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BUGSSUGI 1997 Papers - Index
264 papers. Source: SAS Users Group International conference proceedings.
| # | Title× | Authors× | Abstract× | Keywords× | Extras | Pages |
|---|---|---|---|---|---|---|
| 1 | "How Does Your Data Compare?" SAS's COMPARE Procedure | Jenna Heyen | The COMPARE Procedure is a powerful tool for identifying differences between two data sets because it eliminates often complicated DATA STEP processing. Comparisons can be made at the observation or variable levels and are controlled by using a wide range of options. The ability to choose among six report types and create output data sets increases the value of the Procedure. At William M. Mercer, PROC COMPARE is used to identify differences between a master data set and the master, thereby identifying new data set |
proc compare, proc step, master data management, dataset, data cleaning | source | 4 |
| 2 | "How to Save $30,000 in 4 Hours "-Migrating SAS Systems from the Mainframe to the PC | Iain Robertson | Many companies are looking to use the power of PC's to off-load work from their mainframes. The SAS system is ideally suited to this due to the portability of its code and data and the client/server capabilities of SAS/CONNECT . This paper will discuss how an MVS SAS batch system was converted to run on an |
flat file, raw data | source | 5 |
| 3 | "You Want This New Application to Run on Our VAX, PC and SUN Computers???!!! "(Or Cross-Platform Application Development Using SAS Software) | David W. Franklin | The need for cross-platform applications is increasing as individuals and companies are becoming aware that the future of their own in-house or packaged applications need to be able to work on two or more operating systems, or migrate from one operating system to another quickly and with ease. Investment in time and resources to develop a new application on an existing operating system is often lost when a new operating system is brought in. Rather than loose that investment many adopt the attitude of keep the old operating system going while new software is to be developed on the new operating system. Others though spend significant amounts of time and resources often rewriting from scratch new applications doing the same job that the old application did but in the new operating system | catalog entry, txt, macro variable | source | 5 |
| 4 | %ARRAY: Construction and Usage of Arrays of Macro Variables | Ronald J. Fehd | The SAS software DATA STEP statement array V {3} $ V1- V3 ('A' 'B' 'C'); produces three character variables named V1, V2, and V3 with corresponding initial values, 'A', 'B', and 'C' and a function, dim(V), which returns a value of 3. Programmers can write simple macro tools for use in larger macro procedures. These tools can duplicate SAS software DATA STEP constructions that the programmer is comfortable using and make reading and comprehension easier. The macro statement %ARRAY(V,A B C) produces three macro variables, V1, V2, and V3, with corresponding values: A, B, and C and macro variable DIM_V with the value 3. These variables can then be used in the macro iterative loop statement %DO I = 1 %TO &DIM_V.; This paper examines the SAS DATA STEP array statement and discusses the issues in constructing and using arrays of macro-variables. The macro ARRAY takes parameters of either a list of elements or a data set |
macro variable, array, macro facility, data step, proc contents, macro loop, proc step, macro function | source | 4 |
| 5 | %CHECKALL: A Macro to Produce a Frequency of Response Data Set from Multiple-Response Data | Ronald J. Fehd | Multiple-response data from survey questionnaires where questions have the instruction "check all that apply" present a challenge to the SAS software programmer. For a simple question, the answer may be either A or B; the sum of percent response is 100%. For the series of variables in a multiple-response question, the answer may be both A and B; because response rate for each variable in the series is dependent upon the other variables, the sum of the percent response may be greater than 100%. This paper examines the SAS software PROC FREQ output data set and discusses the construction of a standardized data set containing frequency of response information for multiple-response data for graphics presentation. The CHECKALL macro takes as parameters an output data set name, and a list of the multiple-response /G43 /G43/G68/G65/G72/G72/G79 /G33 /G35/G30/G2e/G30 variables. The output data set contains the variable names and labels of the multiple-response variables |
proc step, proc freq, macro variable | source | 5 |
| 6 | %SHOWCOMB; A Macro to Produce a Data Set with Frequency of Combinations of Responses from Multiple-Response Data | Ronald J. Fehd | Multiple-response data from survey questionnaires where questions have the instruction "check all that apply" present a challenge to the SAS software programmer because the number of possible response combinations is two to the power of the number of responses. This paper examines the SAS PROC FREQ output data set from a cross-tabulation and discusses the issues in constructing a similar data set for multiple-response data with one variable containing the combination of responses. Issues related to labeling, storage and type of multiple-response variables are discussed. The SHOWCOMB macro takes as parameters an output Our output is raw data: the values representing 'checked' data set name which is the prefix of a series of variables and 'not checked' must be mentally translated while containing the multiple-response data. The second reading |
proc freq, proc step | source | 5 |
| 7 | &&&, ;;, and Other Hieroglyphics - Advanced Macro Topics | Christopher Yindra | macro variable, proc step, call symput, macro loop, proc print, run, do loop, symbol table, dataset, proc contents, where statement, macro definition, global symbol table, macro conditional, predictor variable, macro put, sample, macro facility | source | 9 | |
| 8 | A Grid Overlay to Make SAS/GRAPH Layout Easy | Ahsan Ullah | Specifying the placement of graphic components such as annotations and legends can be a time consuming process, since many iterations may be required before the final result is satisfactory. The size and location of graphics elements may change when a graph designed for one device is printed on another. This paper will show how to create a printer dependent template (grid overlay) and how to use it as a guide to create and modify graphs | proc step, sas log | source | 3 |
| 9 | A Macro for Efficient and Flexible Data Smoothing | John Cucka | This macro provides the user with a simple and flexible method for adding data smoothing to their analytical tool box. The user can specify the input data set, the variable to be smoothed, the period of smoothing, and optionally to use center-weighting in the smoothing process. The macro also includes facilities for by-group type processing of stacked groups of data in a single variable | lag function, macro variable, by group processing | source | 4 |
| 10 | A Macro Tool for Quickly Producing a Handy Documented Listing of SAS Data Sets for Use as a Reference While Writing Programs to Analyze the Same | Hugh Geary | Whenbeginning anewprojectI often havea number of SAS data sets with a total of, perhaps, 2000rmore variablesto analyze. Appreciable time can be saved when developing programs for processingthis data if listings canbe made which enable meto scan through the data quickly. This paper describes amacro Iwroteto make listings both informative and compact. The title line has the name of the file in large print followed by the number of records, the number of patients ( or values of themajor sort key), thedateand time the file was last modified and page number. The listings are done by PROC PRINT and are made compact by using small print and printing only as many variables as can be displayed on a page without creating a split page. When a character variable is so long that it will not fit in one page width, my macro automatically breaks it into two variables. Control parameters for PROC PRINT features and other features are passed through macro variables |
proc step, proc print, proc contents, dataset, macro parameter, macro call, macro variable | source | 6 |
| 11 | A Microcomputer Program (SF-36.EXE) that Generates SAS Code for Scoring the SF-36 Health Survey | Ron D. Hays, Cathy D. Sherbourne, Karen L. Spritzer, Wil J. Dixon |
This paper describes a microcomputer, SF36.EXE, that generates SAS code for scoring one of the most widely used measures of health-related quality of life today, the SF-36 TM Health Survey. The SF-36TM Health Survey measures eight health concepts: physical functioning, bodily pain, role limitations due to physical health problems, role limitations due to personal or emotional problems, emotional well-being, social functioning, energy/fatigue, and general health perceptions. The generated SAS code derives the 8 SF-36 TM scales as well as the SF-36TM physical and mental health composite scores. In addition, the program produces code that provides US general population normative scores, age and gender adjusted to one's sample. The significance of the difference between the sample and the general population on each SF-36 TM scale score is also generated. Example input and output files are included | sample, standard deviation | source | 5 |
| 12 | A SAS Based Data Mining Approach to Find Database Solutions in the Banking Industry | Rama Jampani | Faced with intense competition and rising loan delinquency rates, most banks are exploring ways to use their data assets to gain a competitive advantage. This paper demonstrates how the recently emerging data mining technology, if properly utilized, could turn gigabytes of data residing in huge data warehouses into useful information that offers database solutions. The data mining tools and techniques enable end users to develop predictive models, such as neural network models, by capturing the most significant relationships and patterns in a set of data, thereby diminishing the need for statistical training in the process. Neural network models could be developed to prevent fraud, identify credit risks, and provide effective service to customers. The data mining technology encompasses a wide variety of tools and techniques. There is currently no single software package that does it all | data mining, neural network, network optimization, banking | source | 2 |
| 13 | A SAS Macro for Calculating Bootstrapped Confidence Intervals About a Kappa Coefficient | Robert A. Vierkant | Cohen's kappa coefficient has become a standard | sample, confidence interval, bootstrap, sample size, proc calis, weighted kappa, proc freq, cohen's kappa, proc step | source | 5 |
| 14 | A SAS Programmer's View of the SAS Supervisor | H. Ian Whitlock | This tutorial answers questions like: As a DATA STEP programmer, what do I need to know about the SAS supervisor and why? How does the SAS supervisor process DATA STEP code? How does a SAS MERGE work? What about engines, indexing, and views? What happens when my DATA STEP code contains macro variables? What if my DATA STEP invokes a macro or is contained in a macro? For many years Donald Henderson or one of his colleagues gave a tutorial about the SAS Supervisor (SUGI 8, and 12 - 17). This tutorial builds on those earlier articles and adds the experience of the author |
macro facility, by group processing, where statement, character variable, automatic variable, proc step, dataset, macro variable, macro definition, input statement, proc sort, proc sql, rename statement, array, data step | source | 11 |
| 15 | A Standard Adverse Event Summary Report Generation | Frank Liu | adverse events, adverse event summary, create table, proc sql | source | 7 | |
| 16 | A Step-By-Step Illustration of Building a Data Analysis Tool with Macros | Diana Zhang Wobus, John Charles Gober |
Grouping observations in a data set into subgroups according to their percentiles based on a continuous variable (expense, age, or score) and then generating statistics for each subgroup can be tedious. By applying macros appropriately, however, one can achieve greater program efficiency and error-proof | proc step, proc univariate, macro variable, proc means, proc rank, macro loop, macro definition, call symput | source | 7 |
| 17 | Adapting a SAS System Training Program to the Job Market | Barbara B. Okerson | SAS training in an academic environment traditionally reflects the resources available, the required use of the software for academic purposes, and special research related topics by request or as time allows. However, academic use of the software often does not reflect real world situations and requirements for prospective employers wishing to employ SAS programmers. Based in part on a four-year study analyzing specified experience and training requirements from local recruiters and job postings on the Internet, The University of Memphis has altered its SAS training program to reflect real world requirements. Specifically, the University has added support, training materials, handouts and short course offerings in applications development, SAS/EIS, and data handling to the present SAS training program. Since SAS code is portable, an effort is made to provide training and training materials that can be used across a variety of operating systems |
sas programmer, sas programming | source | 4 |
| 18 | Advanced Features of PROC REPORT Workshop | Kim Kolbe Ritzow | PROC REPORT DATA=STOREDAT NOWINDOWS; This workshop is designed for users who have an COLUMNS STORE DEPT SALEAMT COMMENT; existing knowledge of PROC REPORT's syntax. The paper will focus on uses of the FLOW option, the DEFINE STORE/DISPLAY ORDER=FORMATTED creation of multi-column reports, customized report 'STORE'; breaks, and creating reports containing counts and DEFINE DEPT /DISPLAY ORDER=FORMATTED percentages. 'DEPT'; |
proc report, proc step, character variable, proc format, put statement | source | 11 |
| 19 | Advanced MATCH-MERGING: Techniques, Tricks, and Traps | Malachy J. Foley | Match-merging, or BY merging, is the most common merging technique used in SAS**. Yet, how it works is not always obvious. This tutorial shows many of the technique's nuances and subtleties, gives examples of merges where even experienced programmers have been tripped up, and demonstrates defensive programming strategies | by group processing, merge statement | source | 8 |
| 20 | Advanced MATCH-MERGING: Techniques, Tricks, and Traps | Malachy J. Foley | Match-merging, or BY merging, is the most common merging technique used in SAS**. Yet, how it works is not always obvious. This tutorial shows many of the technique's nuances and subtleties, gives examples of merges where even experienced programmers have been tripped up, and demonstrates defensive programming strategies | by group processing, merge statement | source | 8 |
| 21 | Advanced Techniques for Reading Difficult and Unusual Flat Files | Kim L. Kolbe Ritzow | input statement, length statement, do loop, trailing @, flat file, infile statement, dataset | source | 9 | |
| 22 | All the Data That Fits, We Print | Janet E. Stuelpner, Elizabeth Kaptsanov |
How many times do we want to print off a sample of data from a whole SAS (@) database? The first thing you do is to run a PROC CONTENTS and then figure out what the names of all of the data sets are before writing all of the PROC PRINTs to print off some data or even the whole catalog. It is tedious and time consuming. The other thing to consider is that typing in the name of each data set manually is prone to error. This paper will explore several ways in which to capture the names of the members of a SAS catalog and then using macro language, create a program to print off data samples |
proc step, proc contents, sample, proc sql, catalog | source | 3 |
| 23 | An Alternative Method of Transposing Data without the TRANSPOSE Procedure | Sunil Kumar Gupta | class variable, proc transpose, proc step | source | 3 | |
| 24 | An Application of the Internet-based Automated Data Management System (IADMS) for a Multi-Site Public Health Project | Michele G. Mandel, Robert E. Schwartz Jr., Steven A. Kinchen |
Prevention (CDC) began a multi-center case-control study of breast cancer risk factors, focusing especially on risks associated with use of oral contraceptives and other steroid hormones. Data collection for the study, which is already in progress, will last four years. The study is a collaboration between the National Institutes of Health, National Institute of Child Health and Human Development (NICHD), CDC, five field sites, and a data management contractor. Initially, data processing relied on diskettes and mainframe tapes to transfer data among field sites, the data management contractor, and CDC. Data were loaded onto the CDC mainframe and processed in a batch environment. The growth of the Internet and the availability of the SAS System on a UNIX workstation led to a redesign of the data processing protocol and development of the Internet-based Automated Data Management System (IADMS) | libname statement, data wrangling | source | 6 |
| 25 | An Experiment Analysis System for Fixed and Random Effects in OverDispersed Binomial Responses in Semiconductor Manufacturing | Jose G. Ramirez, Randall S. Collica |
In order to manufacture the worlds fastest commercial microprocessor chips (Alpha products) extreme process control and improvement methodologies are required to obtain desired performance and cost. At Digital Equipment Corp. we use SAS GUI interfaces for process experiment analysis of chip probe data. This paper presents how one can model the binomial chip responses from wafers which have received special process treatments in order to characterize and improve the process. Often, process experimenters will repeat an experiment on different lots (batches of wafers grouped together) and thus the effects of lot-to-lot variability is needed in the experiment analysis methodology. We show in this paper how to start with a very simple simplistic view of the data in a designed experiment and progressively add complexities which mimic reality much closer. We show that if one ignores these complexities, the results of an analysis can be rather misleading or even completely reversed | logistic distribution, logistic regression, binomial distribution, regression analysis, proc step, proc genmod, odds ratio, proc mixed, box plot | source | 6 |
| 26 | An In-House Method of Teaching SAS to Fisheries Biologists | Teresa Wilson, Jeffrey Foltz |
Four SAS programming workshops were developed in-house to meet the needs of the freshwater fisheries biologists in the South Carolina Department of Natural Resources. The instructor (primary author) designed the courses and created workbooks with examples and exercises relevant to fisheries research and management. Overall response from the participants indicated that the hands-on approach to learn SAS programming was beneficial | proc step, sas programming, dataset | source | 3 |
| 27 | An Introduction to Developing Applications with SAS/AF Software FRAME Entries | Vincent L. Timbers | Frame entries in SAS/AF use graphic display devices that enable application developers to easily build interfaces which permit users to point and click their way through applications. The functionality of frame entries allow end-users with limited computer experience to easily perform activities such as data entry, data processing, and data analysis/reporting. This paper briefly explains frame entry concepts and demonstrates the steps used in building a sample reporting application with frame entries. 1 INTRODUCTION are for submitting the report for processing, printing the SAS/AF frame entries allow developers to build graphic- oriented applications by placing objects such as icons, push buttons and list boxes in a window with the different objects having different functions. Graphic text and text label objects display text which can not be changed by the user. Text entry objects accept user input and display information or program output |
sample, sas output | source | 7 |
| 28 | An Introduction to SAS/ASSIST Software | Linda P. Atkinson | regression analysis, proc means | source | 6 | |
| 29 | An Introduction to SAS/FSP Software | Terry Fain, Cyndie B. Gareleck |
SAS/FSP is a set of procedures used to perform full-screen interactive data entry, data editing, data retrieval, and data query. This tutorial provides a basic overview of SAS/FSP software under version 6.11 of the SASIB System. Topics include: ● ✎ ✎ ● ✎ creating a new SAS data set customizing data screens data entry data query browsing SAS data sets The focus of this tutorial is on PROC FSEDIT although other procedures such as PROC FSBROWSE and PROC FSVIEW will be briefly discussed. Screen control language (SCL) is considered an advanced topic and will not be covered in this tutorial |
proc step, dataset | source | 5 |
| 30 | An Introduction to the DATA Step Graphics Interface | Earl R. Westerlund | <= 6 1.5-2.5: 6 > 2.5: 6 This is a kind of graphic we use at Kodak to evaluate the color balance of photographic materials. We wanted the ability to generate such a graph within the SAS System, as part of a researcher's or engineer's analysis. None of the standard SAS/GRAPH procedures could easily pro- duce this, however. Our solution was to write a DSGI program |
proc greplay, dataset | source | 6 |
| 31 | Application Development Templates in SAS/AF | Carl R. Haske | Proper applications are logically divided into layers. This division allows the developer to derive generic templates that are reusable in different types of software systems. Templates promote the logical organization of applications into generic and application-specific elements. Templates also enhance usability because they give applications a consistent presentation. For the developer, the advantages of using templates are rapid application development and consistency across multiple applications. The consistency provided by templates contributes to a reduced learning curve for end users as they become familiar with many applications developed with use of the same templates. Standard templates handle system level details like registering users, maintaining a data dictionary, tracking system activity with an error log, typical database management functions, and typical dialogs with the user. Templates also provide default behavior in an application | sample, data dictionary | source | 6 |
| 32 | Automated Generation of a SAS Macro Cross-Reference Table | Connie Bryant | source | 6 | ||
| 33 | Automated Testing of SAS System GUI Applications | Brad Chisholm | Graphical User Interface (GUI) applications present a numberof challengesto softwaretesters,including test execution time, result verification, and repeatability. This paper will give an overview of some techniques and tools used by SAS Institute's Quality Assurance (QA) department to automatetesting of SAS/AF and other SAS System GUI products, such as SAS/GIS and SAS/SPECTRAVIEW . Included will be a discussion of SAS Institute's interactive test capture and replay procedure, techniques for verifying on-screen objects, and screen image captures and comparisons using the Image Data Model Class. Finally, there will be a discussion of industry standard GUI test automation products, such as Mercury Interactive's XRunner and Segue's QA Partner, and their applicability for testing SAS System GUI applications |
data cleaning, sample | source | 5 |
| 34 | Automatic Generation of SAS/ACCESS Views from Oracle Tables | Xinsheng Lin, Sheng Luo |
The authors have been involved in creating large SAS Access Views from Oracle database ( about 30 tables and hundreds of columns) while the Oracle tables are still in development stage. That has required constant change in the SAS Access View as | proc sql, oracle, sample | source | 6 |
| 35 | Basic and Advanced Uses of SASDates | Kenneth L. Goodwin | if-then-else, datepart | source | 5 | |
| 36 | Becoming a SAS Master | Ginger Carey, Helen D. Carey |
proc sql, proc step | source | 8 | |
| 37 | Beyond Field Validation: Incorporating the Batch Edit Into the Total Data System | John A. Quarantillo, Judy Rayner |
Computer Systems professionals have always been faced with the problem of 'dirty data'. In the past, errors were detected using batch edit programs to identify errors. The output from these batch edits was then reviewed, corrections were transcribed onto coding sheets, then keyed, and finally applied to the data using a batch update program. With the advent of custom interactive data entry systems, many edit checks were built into the data entry system, replacing the batch edit process. There are clear advantages to this, but in the interest of speed and simplicity, the data entry edits were not as robust or thorough as the batch edits of the past. Many complex checks were left undone. The approach that we describe uses the SAS system, and SAS/AF to combine a customized interactive data entry system with improved batch systems, taking advantage of the strengths of each to produce an integrated system for data entry and cleaning that is both thorough and easy to use |
data cleaning, dataset | source | 3 |
| 38 | Building a Simple SAS Macro to Generate SQL Instructions in Frequently Used DB2 Tables | Monique Bryher | Writing SQL instructions to extract data stored in DB2 can be made easier through the use of simple coding techniques that utilize SAS macros and the SAS Autocall Facility. Symbolic variables are replaced with values for common SQL expressions in frequently-accessed tables; this has the advantage of minimizing coding time, reducing syntactical errors, affording multiple individuals access to code stored in a "tool kit" of macros that have been tested, debugged, and which can be documented. As will be shown in this paper, these techniques can also be employed to generate large lists in a WHERE predicate that would otherwise be impractical to enter manually | proc sql, create table, proc step, order by, autocall macro, macro put, macro definition | source | 5 |
| 39 | Building an Online Information Processing System Using SAS Software and a UNIX Shell Script | Annie S. Guo, Long Ngo |
At Ischemia Research and Education Foundation, the data stored in the SAS System for UNIX of more than fifteen clinical trials and epidemiology studies have been collected from various sources and systems over the past ten years. The Online Information Processing System is built by integrating base | proc step, clinical trial, proc freq, randomization | source | 6 |
| 40 | Building and Using Macro Variable Lists | Clark Roberts | It is often necessary, in writing programs, to process the same logic over a set of values. Everyone is familiar with the purpose of ARRAYs and DO loops, to apply similar logic to several different variables without repeating the code for each one. The SAS System provides several varieties of DO loop syntax, one in particular, the DO iterative syntax has several flavors, including DO index = list, which is especially useful if the values of the index variable are not contiguous. Unfortunately, this syntax is limited to DATA STEP processing and there isn't any equivalent to this in the macro facility This paper will discuss how to use the SAS Macro facility to emulate the DO list statement for processing a list of character variables that can provide an application with dynamic data driven capability. It will also di scuss different ways that the macro variable lists can be constructed |
macro variable, variable list, macro facility, macro variable list | source | 3 |
| 41 | Building on the Default Line: Sturdy SAS/GRAPH Construction | Susan J. Kenny | title statement, footnote statement, error message | source | 4 | |
| 42 | Calculating and Illustrating the Probability of Developing Cancer Using SAS and SAS/GRAPH Software | Michael S. Zdeb, Matt Dairman |
life table, data step | source | 6 | |
| 43 | CALL EXECUTE-How and Why | H. Ian Whitlock | CALL EXECUTE is a relatively new DATA STEP function which interacts with the SAS Macro Facility. It allows one to send character data to the macro facility for immediate macro execution during the execution of the DATA STEP. It was introduced in SAW3 6.07 and documented in Technical Report P-222 Changes and Enhancements to Base SAS Software. This paper gives examples showing how to use this routine and why you might want to use it. It also explains how macros invoked by CALL EXECUTE behave differently from those invoked via the standard macro call |
call execute, macro facility, macro variable, call symput, proc print, proc step, data step, proc sql, put statement, %if-%then-%else, macro definition | source | 5 |
| 44 | CATALOGER; View, Document, and Compare SAS Catalog Entries and SAS Data Files | Michael Gilman | catalog entry, catalog | source | 6 | |
| 45 | Characterization of Variance in Medical Diagnostics: The Analysis of "Usual" Data | John A. Wass | proc step, sample, proc mixed, outlier, missing value, covariance | source | 5 | |
| 46 | Chart Smart: Design Graphs to Inform and Influence | LeRoy Bessler | bar chart, horizontal bar chart | source | 10 | |
| 47 | Choosing a Method for Connecting Java to the SAS System Across the Internet-CGI, JDBC or Socket? | Larry Hoyle | proc sql, histogram, proc step | source | 8 | |
| 48 | Color Smart: Design Applications for Effective Visual Communication | LeRoy Bessler | source | 2 | ||
| 49 | Combining Display Manager and Batch Mode Under UNIX | John G. Blodgett | The two classic methods of developing and running SAS programs are batch mode and interactive mode using the SAS Display Manager System. Each of these methods has its advantages and disadvantages and most SAS programmers have strong opinions about which is better. We describe a method that we use for running SAS in a UNIX environment that allows us to take advantage of both of these methods simultaneously. By the careful application of a few coding standards and with the help of some custom key definitions in display manager, we are able to utilize the features of the interactive environment for editing our source code and reviewing the results, while we virtually replace the standard SAS "submit" command with our own "batch submit" procedure. We find that using this technique has easily more than doubled our SAS productivity | batch job, sas log, proc step, macro variable | source | 4 |
| 50 | Conjoining Images and SAS Graphics with DATA Step Graphics Interface (DSGI) Navigator | Eric T. Sun | The DATA STEP Graphics Interface provides the graphics routines used by SAS/GRAPH software interactively joined with datasets. SAS programmers can enjoy the 'smooth-sailing' or freedom of creating custom graphs in a DATA STEP programming style. However, just like sailing, there is no freedom without directions. To start a graphic job by selecting a function call such as 'draw line' is much easier than deciding where and how to put it. DSGI Navigator, a SAS/AF Frame Entry application runs with SAS version 6.11 in MS Windows 95, was then designed to ease the task of preparation and maximize the freedom of using DSGI by utilizing the GUI features provided by object classes such as Image and SAS/GRAPH Output. This application currently has three functions, form reproduce, data mapping and graph join. It also produces DSGI source codes after finishing a function through its DSGI program organizer which makes the codes reusable and portable or smoothes the learning steps for novices to DSGI |
dataset, proc step | source | 5 |
| 51 | Constructing ROC Curves with the SAS System | Andrew G. Stead, Karen G. MacDonald |
Medical diagnostics firms manufacture kits to screen individuals for a variety of medical conditions. These kits are designed to detect such conditions based on a test sample from an individual being screened. A particular condition is detected as an abnormal optical density above or below a cutoff value. Before such a kit can be sold, however, the kit obviously must demonstrate good discriminating power between positive and negative samples. It is also necessary to determine where to set the cutoff. Receiver operating characteristic (ROC) curves are often used for this purpose. A | sample, type i error, roc curve, proc step, type ii error, proc freq | source | 4 |
| 52 | Conversion Methods from Oracle to SAS Data Sets Using SAS/ACCESS Software, SAS Macro Language, and the Unix Shell Script | Alex Gaber, Long Ngo |
Massive clinical research data are stored in HP-UNIX Oracle 7.1.6 with SQL/NET V2 tables and managed by Oracle programmers who are unfamiliar with the SAS system. The data need to be converted to SAS data sets for analysis and presentation. Depending on the situation, there are different methods of conversion. Different alternatives were investigated and three methods were compared. This paper demonstrates the following three conversion methods investigated by a SAS programmer with some knowledge of the SQL language and UNIX shell script : - Using Base SAS , Oracle SQL/Plus, and HP-UNIX shell script. - Using the available SAS/ACCESS module in menu-driven mode. - Using the available SAS/ACCESS module in a batch mode. For each of the above three methods of data conversion, the advantages and disadvantages of each method will be pointed out. The SAS code and the UNIX Shell script will also be presented as well as relevant features of SAS/ACCESS and SQL |
dataset, proc sql, flat file, variable, sas base, proc step | source | 6 |
| 53 | Converting an Old MVS Mainframe Project to Run on OpenVMS: A Guidebook to Success | Steven A. Wright | Converting data from one platform to another datasets as MVS SAS tape databases. This can be a trying experience. In general I have made a lot of sense in a pure MVS environment. found that the SAS conversion, per se, is generally straightforward. The bigger problem As we grew, we brought our computing has been the physical moving of the data, resources in house, moving to VMS on VAXes especially when tapes have been involved. This and now Alphas. Until recently, when we paper addresses some of the problems encoun- needed to look at old data, we simply used our tered and chronicles the successes of moving a MVS vendor or had them move the data for us. project from MVS to VMS. However, they have since been bought out and The first hurdle to jump was to find a vendor to do the MVS work needed to convert the project Recently we received a request to retrieve to an ASCII format. Tapes were predictably a seven-year-old project data and compute some source of difficulty | proc step, proc copy | source | 5 |
| 54 | Creating a Home Page on the WWW for Your Local User Group An Unlimited Resource for Local User Group Recruitment Strategies | JoAnn R. Matthews | At the present time, there are more than 200 local or special interest SAS user groups in the U.S. alone, and this number continues to grow. There are, however, only a small number of user groups who have utilized the internet to reach their potential members via a home page. Given the popularity and unprecedented growth of the Internet, the World Wide Web offers an exciting way to publicize local user group activities and increase membership. This paper will discuss step-by-step instructions on how to create a visually attractive and informative home page using some simple HTML (HyperText Markup Language) code. Instructions are also included as to how to link your home page to other regional user groups and SAS Institute | group by, sample | source | 7 |
| 55 | Creating an EIS in Less Than 2 Hours | Deb Cassidy | EIS - Executive Information System - is defiied as 'anintegrated series of applications for information delivery'. SASfEIS@ software provides many 'objects'to let you easily develop your system without having to do custom coding. Participants in this workshop will learn to: - Register data in a metabase for use with SAWEIS - Build the applications using SAS-supplied objects such as: multi-column reports, multi-dimensional reports, 3-D charts, and hotspots on graphics. - Create a menu to link everything together. This workshop is intended for users with no prior EIS development experience or those with only version 6.10 experience. Version 6.11 and Version 6.12 have several changes and additional objects which will be shown in the workshop | character variable, missing value | source | 7 |
| 56 | Creating Client-Friendly SAS Output | Arthur C. Singer, Caroline M. Bobik |
excel, character variable | source | 6 | |
| 57 | Creating Clinical Trial Summary Tables Containing P-Values: A Practical Approach Using Standard SAS Macros | Jun Zuo, Carl R. Haske |
P-value is a key criterion for evaluating the effectiveness and safety of new drugs in clinical trials, particularly in comparative studies. However, p-values are generally not presented in data | proc step, clinical trial, macro definition, macro loop, proc genmod, proc freq, logistic distribution, fisher exact test, logistic regression, proc glm, proc means, dataset, exact test, log-rank test, rank test, wilcoxon rank-sum, %if-%then-%else, regression analysis, proc phreg, wilcoxon test, proc logistic, nominal variable, covariance, adverse events | source | 6 |
| 58 | Creating Column Delimited Files with Little or No Effort | John Charles Gober | When working with large SAS@ datasets containing hundreds of variables and millions of records clients will oflen ask you to create column delimited files to be used on other platforms. Usually to be processed by a third generation language such as Cobol@, PL/I@, FORTRAN@, etc., languages that have been around longer than most database technologies. In many cases the client will ask you to modifi your files by including only certain variables, converting SAS dates to Gregorian or Julian formats, stripping off unwanted decimals. The client may also want you to eliminate white space to decrease file size. And there is always the inevitable change of mind after you are all done, variables that were originally dropped are now to be included, kept variables excluded. States are now to be spelled out instead of abbreviated, and certain variables are now to be placed at the beginning of the record | macro variable, macro conditional, macro quoting function, put statement, delimited file, macro definition | source | 5 |
| 59 | Creating Complex Graphics for Survival Analyses with the SAS System | Steven E. Elkin, William Mietlowski, Kevin McCague, Andrea Kay |
It is frequently of interest to evaluate a therapy across several studies (e.g., meta-analysis) or across several subgroups within a study (e.g. studies with great patient heterogeneity like cancer trials). Comprehensively displaying data from such analyses in a succinct fashion can be difficult two types of unique graphics are presented here with the SAS system. Simulated clinical trial data from an oncology study is analyzed by stratified Log-Rank and standard survival analyses with the PHREGi and LIFETEST' procedures. The primary graph (see figure 1) includes a plot of hazard ratios and their gs~o confidence intervals on a logarithmic scale, observed minus expected values and their variance, event and patient frequencies, stratification categories, and relevant p- values. The Annotate facility and the GSLIDE" procedure from SAS/GRAPH" software enables the presentation of all statistical data to appear along side of the corresponding plot on a single page |
hazard ratio, character variable, proc step, sample, data step, confidence interval | source | 6 |
| 60 | Creating Forms Using the DATA Step Graphic Interface (DSGI) | Harvey Monder | adverse events, dataset | source | 4 | |
| 61 | Creating Graphs Using Templates | Michelle Gayari | Sometimes it is an unnecessary waste of paper or inconvenient to print only one graph per page. Templates are a useful tool for displaying more than one graph, either by overlaying graphs or displaying multiple graphs on a page. Templates can also save time since they can be reused as needed once the template catalog is saved. Using SAS/GRAPH this beginning tutorial will dem- onstrate how to create templates using the GRE- PLAY procedure either interactively or in batch mode, how to use templates, and how to store templates once created. GSLIDE will also be shown as a way to display one title for the entire page |
proc greplay, proc step | source | 5 |
| 62 | Creating Hot-Keys for Data Entry in FSEDIT | Alexa Parliyan | date variable, sysdate9 | source | 2 | |
| 63 | Creating UNIX Network Usage Charts and Displaying Them on an Intranet | Stephen B. Taubman, David Kelly |
Our UNIX Network consists of several sub-area networks (SANs) which are linked together via a common backbone. This paper will describe how we produce charts which display how the computing resources of each SAN are being used. We display the mean and 90th percentile for five measurements of computer usage. The charts are created as gif files and displayed on the Federal Reserve Board's local intranet using HTML programs and the Netscape Web Browser. All work was done on the Sun Solaris 2 operating system using SAS Release 6.11. BASE SAS and SAS/GRAPH as well as the SAS macro facility were used. The raw data is obtained from software supplied by Sun Microsystems. A novice SAS user should understand this paper. The Raw Data The raw data is obtained from software supplied by Sun Microsystems. Monthly raw data files consist of one observation taken every eight minutes for each network machine. Each observation contains 78 variables. A SAS dataset is created from the raw data |
bar chart, raw data, dataset, proc step | source | 4 |
| 64 | Creating Your First Data Entry System Using PROC FSEDIT | Steven A. Wilson | proc step, dataset, catalog entry | source | ||
| 65 | Creation of an Educational Statistics Database at the University of Arkansas | Sean W. Mulvenon, Antoinette Thorn, Charles Aldrich |
The purpose of this project was to address and the use of SAS to complete this goal of creating the needs of the University of Arkansas in and maintaining an educational database. developing an educational database which could be made available for faculty, graduate students, and other community agencies requiring educational The first step in developing this educational statistics and data. The first step in this process was database was to locate data sets which could be the acquisition of data sets from the United States obtained for unrestricted use without violating any Department of Education (DOE) and the National copyright or private use restrictions. One source Center for Educational Statistics (NCES). The identified was the National Center for Educational second, was the writing of a program to create a Statistics (NCES), which is one of 13 divisions of the managed database which would allow consolidation United States Department of Education (DOE) | longitudinal data | source | 3 |
| 66 | Cursor Tracking in SAS/AF FRAME Applications | Don Stanley | error message, exception handling | source | 6 | |
| 67 | Customizing Toolbars | Deb Cassidy | Version 6.11 TS Level 0040 of SAS@ software has a new toolbar for FSP products. While the new icons are an enhancement for many applications, they weren't for one of the applications I support. This paper will give a brief overview of how to customize toolbars for an application | source | 4 | |
| 68 | Data Mining | Mark Brown, John C. Brocklebank |
data mining, neural network | source | 4 | |
| 69 | Data Mining for Hidden Groups in Hospital Populations | Anthony M. Dymond | A data mining case study is presented illustrating exploration for hidden inpatient subpopulations. Some of the major characteristics of data mining and their relation to business goals are reviewed. Six subpopulations are tentatively identified. Two subpopulations correspond to mental illness and alcohol/drug abuse. Four other subpopulations reflect medical and surgical diseases, segregated along lines of major diagnostic category, age, numbers of other diagnoses, and income. Some suggestions are presented for using cluster analysis to find potential hidden groups, and for the interpretation and validation of these groups using visualization and discriminant analysis techniques | data mining, cluster analysis, proc step, sample | source | 6 |
| 70 | Data Mining the Original Data Warehouse: Twenty-Five Years and a Million Lines of SAS Later | H. W. Barry Merrill | libname statement, macro definition, cpu time, decimal, format statement, dataset, datetime variable, proc step, macro variable | source | 12 | |
| 71 | Data Set Management Procedures for Developing a Prevention and Counseling Database | Sean W. Mulvenon, Sherry Ceparich, Barbara Weber, Arlene Metha |
The use of the SAS statistical package has been very interest, and data analysis are simply not avialable at instrumental in the development of two separate the level necessary for most comprehensive studies. databases at Arizona State University (A.S.U.). The The purpose of this paper is to address the issues and databases are the result of studies which investigate procedures utilized in SAS to develop and maintain a the use of various interventions designed at reducing database which would provide solutions to the at-risk behavior in middle and high school students previously mentioned issues when developing and identified as potentially suicidal. The data for each maintaining a large database. subject was collected from numerous agencies and the problem of data management, i.e., the process of merging and organizing the data is the basis for this The use of large databases and the paper. The SAS packages utilized were BASE, management of these databases has become SAS/STAT, and IL |
data governance, ascii | source | 3 |
| 72 | Data Warehouse Implementation with the SAS System | Tony Brown | The successful implementation of a data ware- house can be an extremely complex process, requiring significant planning, patience, and persistence. The Professional Services Division of SAS Institute Inc. has found that a good understanding of data warehousing concepts, coupled with a solid development methodology, and a technical infrastructure built around the SAS System can enable practitioners to achieve their goals of effective data warehousing. This paper addresses many of the challenges and issues that The Professional Services Division has confronted during the development of data warehouses. It explores the definition and | data warehouse, star schema, fact table, dimension table, data cleaning | source | 11 |
| 73 | Data Warehouse: A Telecommunications Business Solution | Demetris Papaiacovou, Larry D. Bramblett, June Burgess |
The telecommunications industry is rapidly becoming the largest user of high volume information systems. This is especially true in the United States, where telecommunications, Internet, video and audio services all fall under the larger umbrella of the information superhighway. Our project team is adept at providing customized business solutions to telecommunications managers by creating specialized information systems to meet their individual needs. We design personalized systems which transcend the traditional boundaries of data warehousing systems by gathering and storing important data, analyzing and transforming the data, and then summarizing and reordering it in accordance with the demands of the user. This provides a dynamic and efficient front- end presentation and reporting tools that transform the users from reactive recipients of hard copy reports to competitive executives poised to make efficient, well informed decisions | data cleaning, data warehouse | source | 4 |
| 74 | Demonstrating Systematic Sampling | Julie Wildman-Pepe | A real data set involving the number of reference requests at a university library, will be used to present systematic sampling as an alternative to daily collection of information. Excessive collection of data is not only very labor intensive but also unnecessary. Data collected during previous semesters can be used as population information. Since true values are known, systematic samples can be generated and results compared to the population parameters | sample, systematic sampling, random sampling, confidence interval, correlation, proc step | source | 6 |
| 75 | Designing Clinical SAS Service Request Forms | Sunil Kumar Gupta | SAS programmers ofien have the responsibility of supporting the reporting requirements of the Clinical AtTairs Department of Pharmaceutical Companies. This involves interacting with department members to define the report. The SAS programmer's task is to understand the request and to design the program to achieve the desired outcome. This is often the most difllcult part of the request. A SAS Service Request Form should be developed to meet the needs of the department and refiect the type of information available for reporting. The fm should be organized to guide the customer through a series of questions. Sections on the form should include who the request is from and the required date, the description of the SAS request with the purpose listed, the selection criteria to identifi the population and time period of the report, and the format and organization of the report along with the method of output desired. Finally, the SAS programmer should log the completion date and time | sas programmer, clinical sas | source | 3 |
| 76 | Designing Databases Using a Customized SAS/AF Frame Entry Application | Esther Kwan | A customized SAS/AF application was developed to facilitate the design of a large research database which has to be applicable in three software systems. This paper gives an overview of this innovative SAS application, as it is related to the project work requirements. SAS automation organized and improved the efficiency and accuracy of this database design task |
proc step, label statement, quality assurance, txt | source | 5 |
| 77 | Detection of Model Specification, Outlier, and Multicollinearity in Multiple Linear Regression Models Using Partial Regression/Residual Plots | George C. J. Fernandez | In multiple linear regression models problems arise when a serious multicollinearity or influential outlier present in the data. Failure to include significant quadratic or interaction terms results in model specification errors. Simple scatter plots are mostly not effective in revealing the complex relationships or detecting data problems in multiple regression models. However, partial regression plots are recommended mainly in detecting influential observations and multiple outlier and the partial residual or the added-variable or component plus-residual plots are mainly usefi,d in detecting non-linearity and model specification errors. Neither plots in the standard format fails to detect the presence of multicollinearity. However, If these two plots are overlaid on the same plot with centered Xi values in the X-axis, the clustered data points in a partial regression plot clearly indicate the presence of multicollinearity | regression analysis, predictor variable, proc reg, outlier, multiple regression, scatter plot, macro definition, proc step | source | 6 |
| 78 | Developing a PC SAS World Wide Web Database System | Faith Reneé Sloan | The first few months of 1996 have seen an explosion of new Web-related technologies hitting the cosmnercial marketplace as well as being offered freely at numerous sites on the Web. This is especially true in the world of low-cost Web servers, databases, and Web- database gateway software for desktop/personal computers. It is now quite possible to develop a functional Web site, complete with database applications, on a desktop computer using the SAS System in a matter of hours or a few days -- and often with only a small financial investment. This paper presents and describes in detail such a systern: Developing Educators Resource World Wide Web (WWW) Database System | dataset, macro variable, %if-%then-%else | source | 6 |
| 79 | Developing Risk Adjustment Techniques Using the SAS System for Assessing Health Care Quality in the IMSystem | Yanchun Xu, Andrius Kubilius |
Risk adjustment is a statistical technique that is used to overcome the effect of differences between health care organizations that can influence indicator rates and distort comparisons. In order to provide valid comparative information to hospitals participating in the Joint Commission lMSystem, the data are adjusted for certain characteristics which patients bring to the health care encounter. The objective of risk adjustment is to identify a model which can accurately predict the outcome while controlling for an array of statistically and clinically significant patient risk factors. Logistic regression is used to ascertain the influence of specific patient confounding variables on the binary outcome. This paper will discuss the process for developing lMSystem risk adjustment models using the SAS system from variable selection, model building, model evaluation through applying the risk adjustment model | risk adjustment, logistic distribution, regression analysis, scatter plot, logistic regression, confidence interval, proc logistic, proc step, ordinal variable, stepwise selection, missing value, binary variable, nominal variable, interval variable, likelihood function | source | 5 |
| 80 | Displaying Information from Mainframe SAS Libraries on Your Intranet | Vecdet Mehmet-Ali | proc step, dataset | source | 6 | |
| 81 | Double Data Entry in FSEDIT Using Point-of-Entry Verification | Derek P. Morgan, Michael A. Province |
Double data entry is a proven, heavily used tool for data quality control. Although there are many functions avail- able in SAS/A@, SAS/FSP@ and methods for FRAME entries to reduce entry errors, double entry adds to the overall quality control of the data. This paper describes a |
error message, numeric variable | source | 6 |
| 82 | DW + DM = $avings | Robert J. Scharl, Paul M. Centric |
Data Warehouse. Data Mart. Data Mining. These are all recently created terms that apply to data extraction and decision support based on a solid understanding of the data. Companies have experienced the methodology of Deeming for Statistical Process Control and Continuos Product Improvement. The recent improvements in computer hardware and improved data access has lead to a revolution in the ease of data analysis for decision support. History The word market place has been shrinking since the Industrial Revolution. Industry used to think only in terms of its community, country or continent for supplying services or products. Improvements in communication and transportation have made it possible for a company to compete in a world market. The world market has also made customers more demanding of the product for price and quality | proc sql, data science | source | 7 |
| 83 | Effective Applications of Control Charts Using SAS Software | Robert N. Rodriguez, Sharad S. Prabhu |
quality control, data science | source | 145 | |
| 84 | Effectively Displaying Statistical Results in a High Volume Drug Research Environment Using SAS/GRAPH | Bruce Chinn | In a drug discovery research environment, scientists sometimes perform many experiments in a short period of time to obtain information about drug compounds and it's different concentrations. After analysis, they need a way to scan the results to confirm whether or not the compound has potential. Plotting graphs and summarizing the results enables the scientist to quickly review the information, This paper discusses the use of SAS/GRAPH and some of it's features such as PROC |
proc step, proc greplay, proc gplot, macro definition, regression analysis | source | 5 |
| 85 | Efficiency Ideas for Large Files | J. Meimei Ma, Andrew H. Karp |
proc step, dataset, proc sql, numeric variable | source | ||
| 86 | Empowering SAS Users through a Webpage on Your Intranet | John M. LaBore | SAS users in any organization can benefit from a webpage on their Intranet. This paper describes web browsing basics and assists the user in constructing a basic webpage. Internet websites with useful tutorials and tools will be listed for the budding webpage developer. Potential webpage developers will be provided a framework for SAS-related webpage content and given the uniform resource locators (URLs) for a number of recommended SAS-related sites which can be "linked" into their webpages; plus, the presentation will include an on-line demonstration of an actual Intranet webpage for SAS users | txt, pharmaceutical industry | source | 6 |
| 87 | Enhanced Shewhart Plots Using a Graphics Template and Annotation | Kathy Claude, Joseph J. Guido |
The Quality Reporting System (QRS) was designed to measure and monitor quality of services and resource utilization within Strong Memorial Hospital. Fifteen indicators for nine departments were initially identified to be followed. Each indicator for each department required a statistical process control chart (SPC), an interpretation section and a comment section. To reduce the amount of paper required to produce the report it was decided to consolidate the three parts of the report onto a single piece of paper per department indicator. This was accomplished by using the GREPLAY procedure to combine a Shewhart plot, an interpretation section and a workspace section into a single graphics output. The ANNOTATE FACILITY was used to create the interpretation and comment sections and to enhance the display of out of control points on the Shewhart plot |
proc step, proc greplay | source | 4 |
| 88 | Enhancing the Output from PROC LOGISTIC | Bharat K. Thakkar, Kwan Hur, Charles A. Oprian, William G. Henderson, Sharon Urbanski |
A SAS@codefor enhancing the output from PROC LOGISTIC with the stepwise option was developed. Among the enhancementsprovided are: the suppression of SAS output fkom several pages to one table, the incrementalchange in the c-index statistic, the -2 LOG likelihood statistic (-2 log L statistic), and an incremental test for the significant change by using the -2 log L statistic. In additio~ the code provides the parameter estimate, the standard error, the Wald chi- square, the p-value of the chi-square, the standard~ed estimate, and the odds ratio at each step of the stepwise logistic regression output |
logistic distribution, likelihood function, sas output, logistic regression, dataset, predictor variable, regression analysis, proc calis, response variable, proc step | source | 6 |
| 89 | Errors, Warnings, and Notes (Oh My) A Practical Guide to Debugging SAS Programs | Lora D. Delwiche, Susan J. Slaughter |
put statement, missing value, sas log, if-then-else, error message, character variable, input statement, infile statement, proc print, proc step, dataset | source | 10 | |
| 90 | Estimating Nonlinear Systems Using Customized SAS Macros: A Study on Demand for Medical Products and Services in the U.S. | Jun Zuo, Guijing Wang |
Two statistical procedures in SAS/ETS, PROC MODEL and PROC SYSNLIN, can be used to estimate nonlinear systems. However, it is often inconvenient for users or researchers to revise SAS code in order to add one or more new variables (or one or more equations) into some specific, common-used, and complicated nonlinear systems, such as complete demand systems. Also, it is always difficult to obtain the standard errors of some indirect parameters, which are calculated based on their nonlinear relationships with the estimated (direct) parameters of the nonlinear systems. Various customized SAS macros are developed in this paper for users to conveniently incorporate new variables into a specific nonlinear system, the Almost Ideal Demand System Model (AIDSM). The bootstrapping approach is one of SAS macros to calculate standard errors of elasticities, which are nonlinear functions of estimated parameters of the nonlinear system |
proc calis, macro definition, price elasticity, proc step, model training, proc model, bootstrap | source | 6 |
| 91 | Estimation via EM-Algorithm in a Bivariate Random Effects Model | Amrik Shah, Kirk A. Easley |
This paper considers estimation in a bivariate random-effects model allowing for arbitrary measurement times and variation in the number of observations for different individuals in the context of longitudinal studies. Two different structures for the covariance matrix of measurement error are considered, uncorrelat ed error between responses and correlation of error terms at the same measurement times. The estimation of parameters for this model is via the EM-Algorithm. We derive the set of equations for both ML and REML estimation when the observed data consists of complete pairs. These equations are encoded in a SAS Macro utilizing SAS/IML for implementation of the methodology. This is illustrated with an example from AIDS clinical trials. KEY WORDS: EM-algorithm, longitudinal data, multiple response, random-effects, REML estimates, SAS Macro |
likelihood function, covariance, restricted maximum likelihood, residual, proc mixed, maximum likelihood estimation, macro definition, missing value, correlation, clinical trial, macro call | source | 8 |
| 92 | Evaluation of Client/Server Configurations for Analytic Processing | Barry R. Cohen | I participated in a project to design and performance test a statistician's work station in a client/server environment. The mix included Oracle on HPKJNIX servers as the data warehouse, SAS Software for analytic processing, and both the HP/UNIX servers and Windows PC clients as candidate sites for the SAS program execution and data serving. The performance test results were presented in my SUG121 paper. Much time was required in that paper to detail the hardware and software involved, and to simply present the performance results. Little time was available for critical analysis of the findings. I now build upon the information in that paper, taking a critical look at what the performance numbers tell us about setting up a client/server environment for data analysis with SAS Software | dataset, traffic data, data science | source | 10 |
| 93 | Exploiting Java Technology with the SAS Software | Barbara Walters | This paper describes how to use Java technology with SAS software. SAS Institute provides a beta SAS/SHARE*NET driver for JDBC. In addition, we provide classes that allow Java applications and applets to create a remote SAS session, submit SAS statements, and retrieve results generated by the submitted statements. This paper describes how to use these class libraries and address client/server configuration and performance issues |
source | 5 | |
| 94 | Exporting SAS Output onto the World Wide Web | Shi-Tao Yeh, Andrew C. Yeh |
proc sgplot, sas output, sample, macro variable, proc step | source | 5 | |
| 95 | Faster SAS Jobs and Fewer Passes Via Data Step Views | Steven J. First | proc step, sas log, dataset, proc print, flat file, data step, elapsed time, sas library | source | 7 | |
| 96 | Forecasting an Electric Utility's CO2 Emissions Using SAS/AF and SAS/STAT Software: A Linear Analysis | Azharul Islam, David L. Wang |
This paper presents a forecasting model which analyzes and projects emissions for an electricCO2 utility. The linear spline regression model is used to forecast emissions. The model is written on SAS | time series analysis, predictor variable, sas base | source | 5 |
| 97 | Forecasting College Enrollment Using the SAS System | Joseph E. Earley, Archie J. Calise |
The purpose of this paper is to illustrate the use of Several of the SAS System>s forecasting procedures. In part icular, PROC ARI MA, PROC AUTOREG, PROC FORECAST and PROC REG are used to forecast enrollment statistics for one of the colleges of the City University of New York (CUNY) Results from the procedures are compared along with comments regarding the applicability of the procedure for this particular project |
proc step, proc calis, proc forecast, proc reg, regression analysis, estimate, proc arima, proc autoreg | source | 4 |
| 98 | FRAME IT: The Nuts &Bolts of RAD | Marty Brown | master data management, bar chart | source | 6 | |
| 99 | From 50,000,000 Claims to One Analytical File | Louise S. Hadden, Mike Murphy, Alan J. White |
Researchers often confront the fact that the most common repositories of data are the least suitable for careful analysis. This is an outline of a small-area study performed by Abt Associates Inc. under one of its health care study contracts, during which a small mountain of data was turned into information that may be useful to our customer. This paper illustrates the power of the SAS@System for processing a great quantity of disparate data, its statistical analytical capability to make use of this information, and its flexibility for producing quatity tables and graphs for presentation. Some of the examples will be specific to the UNIX operating system. Base SAS, SASIFSPW, SAS/GRAPH@, and SASISTA~ are used in this application. For the purpose of confidentiality, the MSA- Ievel statistics shown in each exhibit are fictitious |
regression analysis, format statement, proc step, insurance claims | source | 6 |
| 100 | From IBM/MVS to PC SAS for Windows, a SAS/AF Frame Entry Application | H. Amy Feng, Sue Nowlin |
This paper describes details involved in the transition of a mainframe, batch mode SAS system to a SAS/AF Frame Entry application using Windows@ point-click techniques. . The Proficiency Analytical Testing (PAT) Program is a joint effort of the National Institute for Occupational Safety and Health (NIOSH) and the American Industrial Hygiene Association (AIHA) to improve the performance of industrial hygiene laboratories. Over 1400 industrial hygiene laboratories throughout the United States and Canada participate. Participants analyze a series of metals, silica, asbestos, and organic solvent samples and receive performance ratings quarterly. These ratings are used by a professional society, AIHA, to accredit industrial hygiene laboratories. The PAT System is a SAS application which manages computer aspects of the PAT program, including database management, data analysis, and report production. The system originally ran under IBM mainframe SAS 607 |
libname statement, proc report | source | 5 |
| 101 | From There to Here: Getting Your Data into the SAS System | Andrew T. Kuligowski, Nancy Roberts |
The SAS System has numerous capabilities to store, analyze, report, and present data. However, those features are useless unless that data is stored in or can be accessed by the SAS System. This presentation will provide an | input statement, proc step, infile statement, proc copy, dataset, character variable, filename statement, libname statement, column input, list input, named input, excel, proc sql | source | 10 |
| 102 | Fuzzy Logic and SAS Software - Do they work together? | Markku V. Suni | Reports typically contain observations according to some criteria. An insurance company might want to list customers paying over x dollars or at most y dollars for an insurance policy. It might be that marketing department needs a report showing the customers with expensive car and boat - which can be deduced by the insurance amount - and insufficient life coverage. The problem is that no matter how we set the amounts x and y we may always miss some interesting (x+1 ) or (y-1) dollar cases. This is unfortunate but cannot be helped as programming logic is rather rigid. We are not hopeless, however There is fuzzy logic that offers a lot of flexibility and there is DATA STEP that offers us all the exiting possibilities of fuzzy logic. We can combine SQL with fuzzy DATA STEP to see that marketing department receives the report, the whole report, and nothing but the report it needs |
data step, proc sql, proc step, life insurance | source | 5 |
| 103 | Generating Data with the SAS Data Set | Andrew J. L. Cary | It is often necessary to create data to test a program or methodology. The SAS software system's DATA STEP and random number generating functions provide a powerful toolbox for generating data. This paper will demonstrate how to generate data for variety of situations using this toolbox |
data step, clinical trial | source | 6 |
| 104 | Generic Methodology in Report Building by Using SAS Macros | Irene Zhao | Irene Zhao, Allergan Inc., Irvine, California SAS programmers in the pharmaceutical industry are frequently under time constraints in generating statistical tables for clinical reports. Most tables are similar in format. If we create a generic table generation program, we can greatly reduce the statistical table generating time. This paper discusses how to create generic statistical tables generating programs for clinical reports by using SAS macro techniques and the REPORT procedure (PROC REPORT). There are two major macro structures used in the provided example, a demographic table program. Each macro determines descriptive and/or inferential statistics for continuous variables and categorical variables |
macro call, proc step, nominal variable, interval variable, proc report, demographics table | source | 5 |
| 105 | Get Hiper About Hiperspaces | Fred R. Forst | SAS@offers the option of using hiperspaces as the standard WORK file under MVS/ESA" as a performance en.tiancement. This paper introduces hiperspaces under MVS, and the applicable SAS options to invoke hiperspace use. Also, attention is given to tuning the use of hiperspaces within MVS (i.e. MVS'5 SRM parameters). Performance gains can be astonishing with little or no work on the part of the user. Finally, specitic case study results will be given. htroduction All SAS jobs (either batch or interactive) use a WORK fik%o store temporary data for the life of the job. The WORK file is normally placed on DASD, or occasionally VfO (MVS's virtual input/output). A SAS job Wuld incur a great deal of time reading and writing data to this DASD worktile if the job manipulates a lot of temporary data. MVS tuning, in general, attempts to reduce or eliminate physical I/O to DASD since it usually constitutes the largest portion of a job's runtime | temporary dataset | source | 6 |
| 106 | Getting Started with PROC LOGISTIC | Andrew H. Karp | logistic distribution, logistic regression, proc logistic, predictor variable, regression analysis, proc step, response variable, odds ratio, estimate, confidence interval, proc reg, null hypothesis, data science, proc genmod | source | 5 | |
| 107 | Getting Started With SAS/EIS Software | Dana Rafiee | source | 8 | ||
| 108 | Graphical and Analytical Tools for the Analysis of Two-Period Crossover Clinical Trials | Jeff A. Sloan, Paul J. Novotny, Charles L. Loprinzi, Suresh Nair |
treatment effect, treatment period, clinical trial, crossover study, proc genmod | source | ||
| 109 | Graphical Solutions for Market Intelligence Internet, Intranets, and The Web | Frederick E. Pratter | proc step | source | 3 | |
| 110 | Graphing: Taking the Mystery Out of Subscripts and Superscripts (The Why Not's and How To's Are Presented) | Lori D. Griffin | This paper covers several different areas of a graph where subscripting and superscripting may occur. For example, when graphing, have you ever had a title that needed a superscripted character or a footnote that needed a subscripted character added? Maybe you need to add a note statement that has a character that is superscripted. There are other areas of a graph, like axis values and axis labels that might also contain a subscripted or superscripted character. The intent of this paper is to illustrate the differences in your code that exist when adding subscripts or superscripts to titles, footnotes, notes, axis labels and axis values. Some of these labeling areas of the graph require alternative graphing techniques in order to accomplish the task of subscripting or superscripting | title statement, label statement | source | 7 |
| 111 | GUI to CRSP and COMPSTAT Data | Peter C. C. Luan | CRSP (Center for Research in Security Prices) data and Standard & Poor's COMPUSTAT data are probably the most often used data for instructional and research purposes in many universities and financial institutions. This paper shares the design, describes the functionality of two graphical user interfaces (GUIs), and details some of the experience of developing these two interfaces | proc step, character variable | source | 4 |
| 112 | Handling the Year 2000 and Other Timely Issues | David E. Beam | A Brief List of some SAS Informats/Formats As we approach the year 2000, smart IS professionals are planning for a successful start of the next century. The SAS System has some of the most powerful date handling capabilities of any software system, and can offer valuable tools to prepare your computer files for the end of the 90's. One of the areas in which SAS Software excels is the powerful capabilities to do sequential date processing. This paper will present a brief overview of how SAS handles dates, and some examples of conversions required to read in a variety of dates. Examples of a several unique date calculation problems will also be presented, as well as a discussion of the year 2000 issues | sysdate9, date variable, macro variable, sample, datepart | source | 8 |
| 113 | Having a Ball with Strings | Ronald P. Cody | substr function, character variable, compress function, proc print, proc step, input statement, numeric variable, translate, put statement, character functions, string functions, upcase function | source | 8 | |
| 114 | How Are All of These Tables Related? - Relational Database Map-RDB-MAP.SAS | Eric R. Losby | This simple, yet highly useful SAS program generates a "relational map" of permanent SAS datasets or SAS/ACCESS views within a common LIBNAME |
proc step, proc transpose, proc print, proc contents, sample | source | 5 |
| 115 | How Many Good Fishes Are There in Our Net? Neural Networks as a Data Analysis Tool in CDE-Mondadori's Data Warehouse | Guido Cuzzocrea, Alberto Saccardi, Giovanni Lux, Emilia Porta, Arianna Benatti |
In Data Analysis, Neural Networks (NN) are not a universal problem-solver, nor a completely user-friendly tool that anyone might consider to obtain the best and quickest answer to the most complex question. In spite of that, it would be wrong to ignore the possible advantages of NN in analysing real-world databases, when prior hypotheses are poor and linear modelling inadequate. In classljlcation problems such as discriminating between heavy buyers and non buyers in Direct Marketing, NN seem to be a powerful analysis tool. Are data manipulation and standard statistics therefore useless? Our experience is that only an integrated approach produces the best results: knowledge discove~ in large databases means goal identljication, sample design, a reduction in data dimensions, variable selection, model building (e.g., NN architecture), simulation and probabilistic error measurement | neural network, response variable, sample, proc freq, test set, training set, logistic distribution, proc step, regression analysis, proc princomp | source | 6 |
| 116 | How Symbolic Variables Can Reduce Code in a Graphics Environment | Monique Bryher | This paper discusses how to g enerate a series of 4- way bar charts that are replayed in SAS/GRAPH when the list of possible values assigned to the independent variable is changeable. Macro language coding removes the necessity of maintaining a hard- coded list that might have to be modified during the reporting period, e.g., monthly, by having SAS assign each value of the independent variable to a symbolic variable, which is then resolved during the production of the graph. This eliminates the need for writing code to create each graph, resulting in a program that is shorter and easier to maintain. Last, examples of code will be given which illustrate the power of using double and triple ampersands derived from data variables to supply information required by graphics language expressions, such as names, labels, titles, and footnotes |
macro variable, bar chart, catalog entry, proc step, macro definition | source | 7 |
| 117 | How To Convert A SAS Data Set Into A Quicken QIF Format File | Helen-Jean Talbott | How To Convert A SAS@ Data Set Into A Quicken@ QIF Format File Helen-Jean Talbott, Commercial Credit Corporation, Baltimore, MD Registration activities for the NorthEast SAS@ Users Group (NESUG) annual conference make use of Quicken@ and SAS software on personal computers. Quicken@ software is very useful for managing financial data for home and small business applications. SAS/FSP@ and Base SAS software are very effective for validated data entry, data management, and report production. The difficulty lies in transferring data from SAS data sets to Quicken files. [n order to import transaction data from software other than Quicken, the data must be available as an ASCII file in Quicken Interchange Format (QIF). The QIF file format is not one of the. standard data conversion formats for SAS software at this time. This paper demonstrates how to write SAS program code to create an ASCII file in QIF file format from a SAS data set |
dataset, sas base | source | 3 |
| 118 | How to Use CD-ROM as a Simplified CANDA | Steven Wong | An application for approval to market a drug requires extensive regulatory agency review from different scientific disciplines, one of which is statistics. Clinical data and statistical software must therefore be transferred to regulatory agencies. The transfer media could vary from the high-tech sophisticated CANDAs (computer-assisted new drug applications) to simple floppy diskettes, tapes, or CD-ROMs containing data and program files. This paper discusses SAS programming techniques that enhance the transfer, especially if a CD-ROM is the desired media. The strategy developed by Matrix Pharmaceutical, Inc. to resolve these issues and some of the problems encountered along the way will be addressed | macro variable, sample, options statement, macro definition | source | 4 |
| 119 | How to Use the SAS/AF FRAME OrgChart Object | Thomas A. Miron | dataset, proc sql, length statement | source | 20 | |
| 120 | Implementing a Dimensional Data Warehouse with the SAS System | Gregory S. Barnes Nelson | source | |||
| 121 | Implementing Balanced Replicated Subsampling Designs in SAS Software | Roland K. Hawkes | The resampling method called balanced replicated subsampling for assessing error variances from complex survey samples is implemented in SAS software. Methods for structuring data files and SAS macros for calculations are discussed. The methods are illustrated with data on livestock ownership, school attendance and children's health, including incidence of malaria, from a survey in rural Zimbabwe | sample, temporary dataset, proc append, random sampling, proc calis, macro definition, proc step, bootstrap | source | 6 |
| 122 | Implementing Distributed SAS Applications via Messaging | Cheryl A. Garner, Tony Dean, Stephanie Reinard |
catalog entry, macro variable | source | 7 | |
| 123 | Incorporating External Data Into the Data Warehouse | Tim Walters | This paper presents ways that an intermediate user of Base SAS (with a little SAS/ACCESS thrown in) can incorporate external data into a data warehouse and report on such data. External data is defined as all data outside the organization's operating systems. Data from the company's spreadsheets can be directly included through SAS/ACCESS. Data from outside the company can be included at a summarized or detailed level by creating match variables and using the MERGE statement. /G2C/G31/G37/G35/G32/G27/G38/G26/G37/G2C/G32/G31 Most data warehouse development efforts focus on freeing the company's data from its operating systems and allowing users to query against the data. While this is a necessary first step in designing a data warehouse, and most users are happy that they can finally access the company's internal data, a data warehouse with only internal data is like undeveloped land: it has intrinsic value, but it's value increases as it is built upon |
proc step, proc sort, data warehouse | source | 6 |
| 124 | Industry Directions and the Impact on SAS Programming | Sally A. Goostrey | There are many issues being faced today by individuals in business responsible for setting information technology directions and strategies. Business is changing so rapidly that there is rarely sufficient time for fully customized application development. SAS Institute Inc. has increasingly incorporated computer science concepts into their product line, opening up new opportunities for increased functionality with the SAS System. Many people have used SAS software for years but have found themselves falling behind its current capabilities. Computer science graduates frequently ask questions regarding the future of becoming a SAS Programmer, especially those who wish to become heavily involved in GUI development and object oriented programming. GUI and RAD approaches to development tend to be contradictory to structured analysis, design and programming | source | 6 | |
| 125 | Information Delivery-A Project Management Approach | Kimberly A. Foster | The purpose of this paper is to provide a strategic | dataset, data warehouse | source | 6 |
| 126 | Integrating the SAS System with other Statistical Applications | George Matthews | Overview of Dynamic Data Exchange As a statistical software consultant in an academic setting, I often find myself responding to questions about which statistical package is best for certain tasks. SAS users tend to want to see their data in SAS, partly because of its familiarity and partly because it offers a powerful data manipulation tool. In many academic settings, other statistical packages are utilized. This paper will explore the aspects of using Dynamic Data Exchange (DDE) as a means of integrating the SAS System with other windows-based statistical packages. Alternate | proc step, proc print | source | 4 |
| 127 | Integrating Windows Clients and the SAS System into the Enterprise | Gary Mehler | To utilize the full potential of SAS System on Microsoft Window, your PC should be fully integrated into your enterprise. SAS System products for the PC provide many client/server architectures that Information System designers can use to access, update and analyze the entire spectrum of enterprise data. SAS System client/server products are introduced in different PC based scenarios and several PC, network and SAS System configuration suggestions are presented to help you get better returns from your hardware and software investment | dataset, proc sql, where statement, sas base, traffic data, excel, proc step | source | 9 |
| 128 | Interactive Sampling Using SAS/AF Frames | Keith Cranford, Don Boudreaux |
This paper presents a SAS/AF application which allows you to sample an existing SAS data set using three common sampling techniques. You may also produce estimates of a population mean and its associated stan- dard error. These estimates use the appropriate statistical sampling theory to adjust for population and sample sizes |
sample, sample size, random sampling, cluster sampling, proc calis, dataset, proc step | source | 5 |
| 129 | Interfacing the SAS System with the World Wide Web | Larry Hoyle | source | 10 | ||
| 130 | Introduction to Building a Linear Regression Model | Leslie A. Christensen | This paper will explain the steps necessary to build a linear regression model using the SAS System. The process will start with testing the assumptions required for linear modeling and end with testing the fit of a linear model. This paper is intended for analysts who have limited exposure to building linear models. This paper uses the REG, GLM, CORR, UNIVARIATE, and PLOT procedures. Topics The following topics will be covered in this paper: 1. assumptions regarding linear regression 2. examing data prior to modeling 3. creating the model 4. testing for assumption validation 5. writing the equation 6. testing for multicollinearity 7. testing for auto correlation 8. testing for effects of outliers 9. testing the fit 10 modeling without code. Assumptions A linear model has the form Y = b0 + b1X + ε. The constant b0 is called the intercept and the coefficient b1 is the parameter estimate for the variable X. The ε is the error term | proc genmod, residual, regression analysis, proc step, proc reg, estimate, nominal variable, correlation, binary variable, outlier, response variable, interaction effect, sample, sample size, proc glm | source | 7 |
| 131 | Introduction to FRAME Entries in SAS/AF Software | John C. Boling | label statement, pointer control | source | 5 | |
| 132 | Introduction to JMP under Windows: Hands-On Workshop Outline | Jenny Aquino Kendall, Al M. Best, Charles E. Shipp |
JMP under Windows is highly graphical, inviting us to interact with our data. Along with graphical tools for data visualization, JMP provides us with sophisticated statistical analyses. This combination of visualization and statistical analysis helps us to make good decisions grounded by a sound knowledge of our data. Because JMP is highly interactive, the best way to learn JMP is to use JMP, so in this hands-on workshop, we will learn how to get around in JMP by working with the JMP data table investigating variables using the Distribution of Y platform and the Correlation of Y's platform analyzing relationships such as ANOVA and simple linear regression with Fit Y by X learning about additional JMP features. Welcome to JMP Since the best way to learn JMP is to use JMP, we'll start by showing you an example based on actual analyses that are typical in the semiconductor manufacturing industry. Then, we'll give you a chance to use JMP and work with that same data | dataset, correlation, box plot, outlier, regression analysis, anova, histogram | source | 6 |
| 133 | Introduction to SAS/ACCESS Software | Dana Rafiee | source | 2 | ||
| 134 | Introduction to Using PROC SQL | Thomas J. Winn Jr. | This tutorial presentation will explain the basic syntax of the SQL Procedure. PROC SQL is the SAS @ System's implementation of Structured Query Language, which is used for retrieving and updating data in relational tables and databases. PROC SQL also has substantial data manipulation and summarization capabilities. PROC SQL statements could be used to replace much traditional SAS code (DATA STEP, PROC SORT, and PROC MEANS steps), resulting in less programming time and greater computer efficiency. Most of the illustrative examp[es in this presentation pertain to DB2 tables which are used for tax administration purposes at the author's agency. The principles underlying each example should transfer readily to other settings |
proc sql, proc step, order by, group by, relational database, dataset, select, sql pass-through, create view, inner join, full join, proc means | source | 7 |
| 135 | Issues Concerning Consultant-Client Interactions: Things I learned at the Information Center | Ioannis C. Dimakos | This paper considers certain fundamental issues whenever a consultant's services are needed. From the beginning, consultants and clients need to agree on several principles, set the parameters of their collab- oration, and communicate clearly their expectations of the other's role. Often problems arise when ei- ther or both parties fail to set some mutually agree- able guidelines and standards of communication. The end result may be a disappointed, dissatisfied, client who may not seek consultation services in the fu- ture and a stressed, overworked consultant who may feel that her/his services are not appreciated. Finally, some random personal notes from my experiences as aS A S consultant working at the Information Center of a major University are presented | clinical research, statistical software | source | 3 |
| 136 | IT Performance Reporting-Breaking Free of the Glass House | Bruce R. McClinton | The concept of a performance management data repository still has a place in the era of Enterprise Computing. However, if it is to be accepted and thrive it must not remain captive of the glass house. This paper addresses issues encountered in gaining acceptance of SAS/CPE from an increasing diverse audience of data users. Also visited are the difficulties of remote reporting of performance data across platforms, and across the network |
data dictionary, capacity planning | source | 3 |
| 137 | It Takes at Least Two to Tango - A Data Set Joining Primer | Caroline C. Bahler | The ability to combine different types of data from multiple hardware and software platforms is a major strength of the SAS@system. SAS has blessed information analysts with a wealth of different options for joining data values from many different data structures. Therefore, an information analyst needs to determine who (parent data structures), what ("software envi- ronment"), where ("hardware environment"), how (the tools available to perfiormthe join) and why (the required contents of the child data set) of a join in order to determine which strategy to use, This paper will discuss the joining tech- niques offered within the SAS system and give examples of their use | proc step, inner join, proc sql, merge statement, set statement, flat file, full join | source | 9 |
| 138 | JMP Reveals the Truth: Statistics Can Be Fun! | William R. Gjertsen | JMP is an interactive statistical analysis program that promotes the visualization and discovery of important patterns and outliers in your data. It accomplishes this through unique graphics and the dynamic linking of points. JMP's charter is to harness both statistics and graphics together at one time so that data analysis becomes understandable, enjoyable, and even fun! The use of leverage plots, desirability and interaction profilers, parallel axis graphs, Gabriel bi- plots, the interactive linking of graphs, and the use of animation, magnifying. lasso, and slider tools will be shown with examples from science, engineering and finance | outlier, standard deviation, sample, data science | source | 11 |
| 139 | Kappa Statistics for Multiple Raters Using Categorical Classification | Annette M. Green | In order to assess the reliability of a given characterization of a subject it is often necessary to obtain multiple readings, usually but not always from different individuals or raters. The degree of agreement among the various raters gives some indication as to the consistency of the values. If agreement is high, we feel more confident the ratings reflect the actual circumstance. If agreement among the raters is low, we are less confident in the results. While several methods are available for measuring agreement when there are only two raters, this paper concentrates on presenting a generalized implementation of the Fleiss (1981) technique. This method can be utilized even in situations where there are more than two raters and/or categories. A review of the statistical theory behind the intraclass correlation coefficients and kappa statistics obtained when looking at the above situations is presented. SAS code is provided which utilizes basic SAS procedures | cohen's kappa, proc step, proc freq, correlation | source | 6 |
| 140 | Learning About Your Data: Tips and Techniques for Looking at Large Files | Sandra D. Schlotzhauer, Bob Anschuetz |
proc step, character variable, proc means, numeric variable, proc contents, missing value, proc print, proc sort, sample, attrib statement, proc compare, clinical trial, binary variable, laboratory data, label statement, pharmaceutical industry, sas log, where statement, obs, cpu time, sorted data, proc freq | source | ||
| 141 | Lending a Hand with SAS Software - An Application in the Banking Industry | Deborah J. Blair, W. Lily Hadinoto |
Fair Lending issues are of paramount concern to the banking UNIT=AFF=DDname, and specifing the previous DDName, you industry. This paper describes one technique that CoreStates Bank can use the same tape drive successively. In this program, o nly uses to monitor its' lending practices. In this approach, we use one tape drive is requested, instead of two. This can be cruc ial to JCL, Job Control Language and Base SAS on an IBM mainframe. efficiency in some environments. Geared towards the novice SAS programmer, two procedures, PROC SQL and PROC REPORT are key to this program. This //CL9741BY JOB (009978),'HADINOTO-L.1-9-2-4', paper details a real-world problem and offers a simple, yet // MSGLEVEL=(2,1),NOTIFY=CL9741, innovative solution. // MSGCLASS=N,CLASS=I |
if-then-else, proc step, proc report, macro loop, %if-%then-%else, macro definition | source | 6 |
| 142 | Let's Not Forget E-Mail | Jack N. Shoemaker | isp, probability distribution | source | 6 | |
| 143 | Loading SAS Data in Informix: An Integrated Approach | M. Kumar Sagar | In a typical clinical trial, especially large and/ or multicenter ones, there are many sources of data, including electronic data transfers from sites, central labs and CROs. While the data may come in many formats, the question arises: how to load these data in to appropriate databases. In this context, we have taken a holistic approach whereby SAS is used as the platform of choice to deal with these data transfers. SAS transport datasets coming in are converted to host SAS datasets, and required data transformations and manipulations are applied. Once the data is in the desired format, an output file is written and then, using SAS/ACCESS for Informix, an Informix table is created and populated with the data from the SAS datasets. In this process, UNIX utilities are also used as an umbrella, to perform various tasks such as input verification, error checking, invoking SAS programs, cleaning the data, and to archive the associated files. This |
dataset, proc step, proc sql | source | 6 |
| 144 | Logistic Regression Adjustment of Proportions and its Macro Procedure | Dingyi Zhao | Logistic regression model can be used to calculate the conditional probability that outcome is present as denoted by P(Y=l~X) . To adjust some confounding factors,one can consider using the adjusted proportions. This paper introduces an adjustment method based on logistic regression model and presents its corresponding macro procedure. The macro presented here enables to calculate multivariate adjusted proportions and its corresponding confidence intervals and outputs the results in a tabular form | logistic distribution, macro definition, macro conditional, macro loop, logistic regression, macro variable, proc step, regression analysis | source | 6 |
| 145 | LOGITSE: A SAS Macro for Logistic Regression Modeling in Complex Surveys | Jesse Albert Canchola, Brian D. Marx, Joseph A. Catania |
Traditional formulae for standard errors and subsequent statistical significance tests implemented in various popular statistical packages are based on the premise that the data are a simple random sample (SRS) of observations from a super- population. Equivalently, the observations are assumed to be independent and identically distributed (IID). For complex analytic surveys, these assumptions are almost always invalid leading to potentially incorrect inferences due to the failure to adjust relevant standard errors of the parameters. Here, we concentrate on binary responses where a logistic regression analysis would be meaningful and introduce a SAS macro, LOGITSE, that takes the cluster-correlated nature of the complex survey design into account, thus providing for correct inference | logistic regression, logistic distribution, design effect, regression analysis, proc calis, sample, predictor variable, random sampling, response variable, dataset, covariance, likelihood function, significance level, confidence interval, macro definition, correlation, proc logistic, binary variable | source | 6 |
| 146 | Macro and Sample Source Code to Wrap Character Variable Text Conditionally on Two Lines Within Data Null-generated Report Column(s) | Robert Andresen | The wrap macro requires knowledge of base SAS @ software Data _NuH_ processing, SAS fimctions, and SAS Macro Language, and can be utilized anywhere that Base SAS and SAS Macro Language are available. Macro design assumes that report generation uses a DATA _NULL_ to write one observation per line in multiple columns, and that some character variable values are accommodated on two lines, rather than one, within a column. The programmer can store the macro in a macro library or copy it into a program. When invoking the macro, the programmer supplies parameters, such as the width of the column, the character variable to "wrap", and whether to indent the second line. If the text cannot fit within the column, the macro sets a flag to so indicate, and divides the text between two programmer-supplied variables whose length equals the column width. After filling the first variable, the macro assigns the overflow (splitting the text at a space or dash) to the second variable |
character variable, sample | source | 3 |
| 147 | Magic with CALL EXECUTE | Bob Virgile | call execute, proc step, macro loop, macro definition, %if-%then-%else | source | 2 | |
| 148 | Managing Disk Space with SAS | Greg Mast | I have been involved with managing a growing number of SAS users in a VMS environment. While the number of users has increased, the amount of available disk space has not increased proportionally. I created a BASE SAS reporting tool which has helped me monitor disk space utilization by user and by the type of file. The code is not very sophisticated, but has helped avoid numerous frustrations and delays due to full drives | proc step, macro definition | source | 6 |
| 149 | Managing Large Financial Data with the SAS System and the WEB | Paul J. Ratnaraj | During the past decade, use of large and complex data sets has grown substantially. This usage explosion has compelled schools to experiment with better access and management methodologies for a diverse and dynamic user environment. The Web is poised to be the best medium for delivering data optimally across all platforms. However, the Web is still in its infancy both in terms of its use and the tools required to develop stable applications. Wharton was one of the pioneers in using SAS for information delivery in an academic environment. In 1993 we started using SAS to manage the delivery of our data. In late 1995 we started providing access to large financial data sets using SAS and the Web. This paper highlights our transition from using FORTRAN based delivery mechanisms to our current data delivery paradigm. Additionally, this paper discusses the Web and its components, like CGI scripts, HTML, and Java, and the importance of security | http, credit card | source | 10 |
| 150 | Manipulating Clinical Research Data with the TRANSPOSE Procedure in SAS/ASSIST Software | Stanley Cron | proc transpose, clinical research, frequency analysis, proc freq | source | 2 | |
| 151 | Map in an App: The Power of GIS Software in SAS Applications | Dave Jeffreys, Aaron Hill, Lisa Weber |
Map in an App: The Power of GIS software in SAS Applications by Dave Jeffreys, Aaron Hill & Lisa Weber SAS Institute inc. In today's competitive business environment, effective business decisions are more critical than ever. The rapid development and use of Geographic Information Systems (GIS) technology allows organizations to improve business processes and enhance decision support by combining leading GIS technology with business data. With map (spatial) and demographic (attribute) data becoming less expensive and more accurate, more organizations are looking at business geographies applications to gain a competitive advantage. Business geographies applications provide a powerful interface for exploring business data such as sales, competition, and demographic information through an intuitive mapping environment | source | 4 | |
| 152 | Map Smart: Design and Build Effective InfoGeographics Using PROC GMAP and Software Intelligence | LeRoy Bessler | macro conditional, proc step, if-then-else, proc gmap, macro definition | source | 10 | |
| 153 | Measuring The Information Con ten t Of Regressors In The Linear | Joseph Retzer, Kurt Pughoeft |
This pap er b egins b y describing an implemen tation of Krusk al/'s relativ e imp ortance analysis using SAS ST A T and SAS IML/. While Krusk al/'s w eigh ts lend insigh ti n to the relativ e imp ortance of eac h regressor/, they are non/-additiv e in nature and therefore limit p oten tial in terpretation/. In order to o v ercome the non/-additivit y dra wbac k/, an information theoretic measure /#28as suggested b y Theil and Ch ung in /#5CInformation/-theoretic measures of /#0Ct for univ ariate and m ultiv ariate linear regressions/"/, The A meric an Statistician /1/9/8/8/#29 is implemen ted/. In addition/, the impact of regressor v ariable collinearit y is examined using sim ulated data/. This pap er is targeted to w ard exp erienced SAS users familiar with PR OC REG in SAS ST A T/. Additional bac kground kno wledge of statistical concepts/, particularly with resp ect to partial correlations and regression analysis is also recommended/ |
source | 6 | |
| 154 | Measuring the Information Content of Regressors in the Linear Model Using PROC REG and SAS/IML | Joseph Retzer, Kurt Pflughoeft |
source | 13 | ||
| 155 | Meta Data Designer-A Tool for Setting Up Meta Data for a Data Warehouse | Sy J. Truong | data warehouse, proc step, clinical trial, proc contents, proc sql | source | 5 | |
| 156 | Mining the Data Warehouse: Statistical Analysis of Combined Tables of Categorical Data | Gilbert W. Fellingham, H. Dennis Tolley |
W e illustrate a maxim um lik eliho o d metho d for pa/- rameter estimation in com bined tables of categorical data/. Often/, not all cells will con tain data when m ul/- tiple tables are com bined/. Also/, since the same lev el of aggregation o v er co v ariates is often not a v ailable in eac h of the constituen t tables some data will exist only on the margins/. The metho d w e presen t is ap/- propriate when data for some cells are missing/, and ev en when data ma yb e a v ailable only on the margins/. T o illustrate the metho d w e com bine mortalit y tables from three di/#0Beren t sources with di/#0Beren t classi/#0Cca/- tion information/. The co de for the analysis is pre/- sen ted in SAS Pro c IML/, a p o w erful dev elopmen tal to ol for this t yp e of analysis/. /1 In tro duction The purp ose of this pap er is to demonstrate a sys/- tematic metho d of com bining data from di/#0Beren t ta/- bles/ |
source | 6 | |
| 157 | Mining Your Data for Health Care Quality Improvement | Greg Rogers, Ellen Joyner |
Quality improvement in the health care industry can best be defined by examining the driving forces that are effecting the industry. The evolution of the health care in this country is driven by a single purpose. How can health care organizations lower cost, raise quality, and still remain competitive? The implementation of patient-focused quality improvement programs are at or near the top of the list for both information technology (IT) and business unit managers alike in their efforts to lower cost. For IT managers, the key benefit SAS software brings to the table an environment of seamless integration of tools, data, and solutions across the enterprise. Data is at the heart of any patient-focused quality improvement program. The SAS System's access methods and data warehousing capabilities give IT managers what they need to implement the infrastructure necessary for a successful quality improvement and data mining solution | data mining, neural network, proc hpsplit, sample, data governance | source | 7 |
| 158 | Model Selection in Linear Mixed Effects Models Using SAS PROC MIXED | Long Ngo, Richard Brand |
Although there are disadvantages associated with model building procedures such as backward, forward and stepwise procedures (e.g. multiple testing, arbitrary significance level used in dropping or acquiring variables), many analysts use these procedures and are not aware that alternative modeling selection methods exist. This paper focuses on model selection using the Akaike Information Criteria (AIC) in the case of linear mixed- effects models. AIC' s fundamental concepts are reviewed and two examples are given to demonstrate its use through PROC MIXED. Master-level biostatisticians, epidemiologists, and others who are working with longitudinal data are encouraged to investigate AIC as the tool in modeling repeated measures data. 1.0 Introduction Model selection is one of the most frequently encountered problems in data analysis |
feature selection, covariance, covariance structure, likelihood function, proc mixed, maximum likelihood estimation, compound symmetry, repeated measures, proc step, restricted maximum likelihood, longitudinal data | source | 6 |
| 159 | Moving VMS Data to MS-EXCEL: Using SAS/CONNECT Software and DDE to Download Data from a VMS/ALPHA Network to Excel Spreadsheets on a PC | Randall Cates | sas batch, excel | source | 6 | |
| 160 | Multiple Response Optimization using JMP | Daniel J. Obermiller | Typically in the analysis of industrial data there are many response variables (or physical characteristics of the end product) that are under investigation at the same time. Relationships between these responses are quite common, and the analyst must decide which responses are most important, usually at the expense of other responses. Fortunately, there are several techniques that have been developed to allow the simultaneous optimization of several responses. This paper briefly reviews some of the techniques developed for multi- response optimization. The paper also demonstrates several different ways in which JMP statistical software can solve the problem of optimizing multiple responses | contour plot, predictor variable, response variable | source | 7 |
| 161 | Native Help Technology in SAS/AF Applications | John Kruth | Attaching native help to a SAS/AF application can be a complex task. This paper will examine some of the tools and techniques available to both help authors and application developers to simplify this task. Topics will include: Details of the expanded _HELP_ method available in Release 6.12 How the SAS System calculates help topic identifiers for SAS/AF objects, and how you can plan your help system to answer those identifiers How to invoke context-sensitive help for FRAME objects How to provide access to your help system from your application's help pmenu |
source | 4 | |
| 162 | Net Impact Analysis for Program Evaluation, Modeling and SAS Programming | Boqing Wang | This paper discusses alternative methods for estimating the benefits of social programs with an application to Demand Side Management (DSM) in the utility industry | proc reg, sample, likelihood function, proc step, binary variable, logistic distribution | source | 6 |
| 163 | NO MORE MERGE - Alternative Table Lookup Techniques | Dana Rafiee | source | 6 | ||
| 164 | Object Interfaces | Andrew A. Norton | catalog entry, relational database | source | 9 | |
| 165 | Odds Ratios in a Tabular Presentation | Stephen M. Noga, Dingyi Zhao |
Odds ratios and their corresponding confidence intervals are easily obtainable statistics using the 'RLJ option in PROC LOGISTIC (SAS@/STAT). However, there is no option to output these statistics to a SAS dataset. This presents a challenge to the user when the task at hand is to present those statistics in tabular form, such as output from PROC TABULATE. This paper uses PROC LOGISTIC, PROC TABULATE, and the SAS Macro language to produce the desired tables |
proc step, logistic distribution, proc logistic, proc tabulate, odds ratio, macro variable, create table, confidence interval | source | 6 |
| 166 | OLE and the SAS System for Windows Release 6.12 | Jennifer Bradshaw Clegg, Carol Williams Rigsbee |
This paper describes the OLE support within the SAS System for Windows Release 6.12. This support includes OLE container, OLE automation con- troller, and OLE automation server func- tionality. OLE container and OLE con- troller support is available in SAS/AF FRAME entries and SAS/EIS applica- tions. OLE automation server support is available with base SAS software |
excel, sas base | source | 10 |
| 167 | On Time and Under Budget: Guidelines for Success Using the SAS System with Traditional Structured Techniques | Marc Daniels, Clark Roberts |
A few years ago, Community Care Network, a provider of services to the health care industry, faced a major crisis. One of the services they provided for trading partners was becoming difficult to deliver on time. Initially, the service was provided on an adhoc basis, which sufficed while the subscribers were few. As business increased, CCN staff were finding it difficult to meet schedule expectations and were in jeopardy of losing their business. The Information Services group recommended developing a system that would provide CCN with a uniform approach to providing the trading partners with a quality product in a reas onable time period. Because of the complexity of the process it was almost mandatory that a traditional structured approach be used in all phases of the project. The SAS System was chosen over C and other alternatives as the development environment | paid loss, outlier | source | 4 |
| 168 | One-to-One Matching Of Case/Controls Using SAS Software | Charles John Tassoni, Baibai Chen, Clara Chu |
In an epidemiological study it is often desirable to transfo rm sepa rate sets of case and control subjects into a single data set in which each case subject is paired with a distinct control/. This p ro cess is called one/-to/-one matching/. Matches a re made based on ho ww ell they re/- duce di/#0Berences b et w een case and control on a p otentially confounding va riable /#28e/.g/./, p rio r health in a drug e/#0Ecacy study/#29/. This a rticle p resents an example of a one/-to/-one matching task and the SAS co de necessa ry to implement it/. The co de consists of D A T A step/, SQL/, and MA CRO p rogramming/. One/-to/-one matching is done in t w o steps/. The /#0Crst step is to /#0Cnd all acceptable controls fo r each case/. The second step is to /#0Cnd the b est match fo r each case/, o r/, failing that/, fo r as many cases as p ossible/. The second step is general enough that it can b e co ded into a macro that do es not dep end on the sp eci/#0Ccs of the example p resented here/ | source | 2 | |
| 169 | Organizing Your SAS Graphs | Steven E. Elkin | Writing programs to run SAS/GRAPH" software has long been a challenging task for many programmers. Understanding how to display, store and print the output are all difficult issues which must be faced even after appropriate SASIGRAPH syntax has been developed. By using standard GOPTIONSi, the GOUT option to store graphs in catalogs, and PROC GREPLAY' to name the graphical entries in the catalog, a simplified method for organizing your SAS graphs is achieved. This method allows for both on-screen displays and printouts of your graph. Additionally, once stored in a SAS catalog, future access of your graph is possible without the need to re- submit the program which originally created the graph |
proc step, proc greplay, catalog | source | 2 |
| 170 | Overcoming Kainophobia: Replacing Complex Merges with PROC SQL | Brenda M. Barber | here are many instances in working with data from clinical trials where TMERGE is not an adequate tool for joining datasets. Often the data must be extensively manipulated prior to the MERGE, and then un-manipulated afterwards. At times, more than one MERGE must be done to achieve the desired effect, or quite possibly, the dreaded hard coding may take place. PROC SQL has changed all that, and it doesn't have to be difficult to use. Beginning with some basic SQL code, this paper will discuss how to "step up" your code to achieve the truly desired outcome |
proc sql, proc step, create table, dataset, adverse events, laboratory data | source | 6 |
| 171 | Performance Testing for SAS Running on AIX and Windows NT Platforms | Paul M. Gilbert, Steven Light, Andy Siegel, Shylendra Kumar |
At Astra USA, Statistical Programmers and Statisticians use the SAS System to produce datasets, listings, tables, graphics and analyses which are the basis for a Clinical Trial Report. SAS software is configured in a distributed UNIX environment using IBM AIX workstations and an IBM RS/6000 mainframe. SAS users have often experienced significant performance degradation, seemingly during hours of peak network and RS/6000 system use. Performance testing is conducted to document and identify the source of AIX performance degradation, and to investigate analagous Windows NT client/server configurations. A secondary purpose is to obtain performance data for several different Windows NT client/server configurations in preparation for selection of a PC-based configuration for running SAS/PH-Clinical. Three AIX configurations and five Windows PC client/Windows NT server configurations are evaluated. Scope The scope of testing is twofold |
work library, macro variable, libname statement, clinical data management, clinical data, data governance | source | 6 |
| 172 | Power Transformations Using SAS/IML Software | Ioannis C. Dimakos | Sample SAS/IML code is presented here that will assist users in performing power transformations to non-normally distributed variables. The code esti- mates a range of values of λ, selects the appropriate value, and assesses the normality of the transformed variable. The macrocode has been tested using SAS software, release 6.09 for Unix platforms, and SAS 6.11 for Windows 95, but should work with other SAS releases, as well. Power Transformations When dealing with parametric statistics, one of the assumptions that must hold true is that the exam- ined variables are normally distributed (Kirk, 1982). SAS users can use the SAS/BASE UNIV ARIATE procedure, with the optional statements NORMAL and PLOT, to test for normality and obtain stem-and- leaf and box-and-whisker plots of the variables' distri- butions |
proc step, proc iml | source | 4 |
| 173 | PROC DATACHK Revisited: The DATACHK Macro | Jeffrey M. Abolafia | numeric variable, proc step, dataset, macro variable, label statement, time. | source | 6 | |
| 174 | PROC FACTOR: How to Interpret the Output of a Real-World Example | Rachel J. Goldberg | This paper summarizes a real-world example of a factor analysis with a VARIMAX rotation utilizing the SAS@ System's PROC FACTOR procedure. Each step you must undergo to perform a factor analysis is described -- from the initial programming code to the interpretation of the PROC FACTOR output. The paper begins by highlighting the major issues that you must consider when performing a factor analysis using the SAS System's PROC FACTOR. This is followed by an explanation of sample PROC FACTOR program code, and then a detailed discussion of how to interpret the PROC FACTOR output. The main focus of the paper is to help SAS software beginning and average skill level users learn how to interpret programming code and output from PROC FACTOR. Some knowledge of Statistics and/or Mathematics would be helpful in order to understand parts of the paper. All of the results discussed utilize Base SAS and SAS/STAT@ software |
proc factor, proc step, factor analysis, scree plot, exploratory data analysis, sample, data science, orthogonal rotation, r-squared, varimax rotation, correlation | source | 5 |
| 175 | PROC FSVIEW: A Real Programmer's Tool (Or A Real Programmer Doesn't Use PROC PRINT) | Marge Scerbo, Alan C. Wilson |
Although SAS/FSP@ is often regarded as the domain of application developers using SAS/AF@, SAS/EIS@, SCL and FRAME, new enhancements have made PROC FSVIEW an efficient and effective tool for programmers and researchers to browse and edh data, debug SAS code, perform multi-level queries on-line and create reports and new data sets interactively. An on-line demonstration will show subsetting with WHERE and WHERE ALSO clauses, interactive SORTing, and rearranging the displayed columns as scrolling or ID variables. This tutorial will also include examples of modifying existing variables and creating new variables interactively using FSVIEW formulas. In addition, and perhaps most importantly, the when and why to use PROC FSVIEW will be discussed |
proc step, where statement, proc print, dataset | source | 7 |
| 176 | PROC GMAP: How I Learned to Tolerate (and Almost Love) Annotating | Keith J. Brown | proc step, proc gmap | source | 6 | |
| 177 | PROC REPORT: An Introduction to the Batch Language | Ray Pass | proc report, proc step, sample, proc print, class variable | source | 10 | |
| 178 | Putting Yourself on the Map with the GMAP Procedure | Michael L. Davis | Many users are fascinated by maps although they seem too complex to be produced by an average user. This paper introduces to new SAS/GRAPH users the concepts necessary to create maps. The paper offers guidance in finding those pesky coordinates required to put the GMAP procedure to work. The major features of PROC GMAP that are required to draw a geographic map are explored. The paper also discusses elements of good graphic design as they apply to maps, and presents tips on using graphic devices and drivers intelligently. Part 1 |
proc step, proc gmap, sample, dataset | source | 10 |
| 179 | Puzzles in 2D and 3D Visualized with DSGI and Perspective Mapping | Ted Clay | Do you enjoy puzzles? SAS@ can be used to solve not only abstract problems but also the physical kind of puzzles you can hold in your hand. An algorithm is presented which finds all possible solutions to puzzles which require fitting a collection of pieces in various shapes into a limited space. This is applied to (1) Pentaminos, a flat puzzle with 12 pieces to be fit into a 6x1 O rectangle, and (2) a 3x3x3 cubic analog to Pentaminos. Solutions are presented using SAS/GRAPH@ and its DSGI component |
data step, proc gplot | source | 5 |
| 180 | Quantitation of Interactive Effects between Anticancer Agents Using SAS Macros and SAS/GRAPH | Yalan Wang, Jun Zuo, M. Guill. Wientjes |
The interactive effects of two anticancer agents are frequently evaluated using three different types of graphs: concentration- effect curves, isobolograms, or combination index curves. In order to determine the cytotoxicity of the combined agents at an array of combinations, the experimental cytotoxicity data are usually processed by using statistical software and spreadsheet software separately. In general, the use of separate software applications is time-consuming and introduces the risk of errors made during data transfer. To avoid these pitfalls, we developed a SAS based system that processes the raw cytotoxicity assay data and generates three types of graphs and related parameters. The system consists of a series of SAS macros that can be structured in three levels (menu program, main flow macro, and individual function macros) and classified into three categories (data manipulation, model estimation, and graph presentation). Three curves are generated using SAS/GRAPH |
macro variable, model training, sas base, raw data, macro definition, standard deviation, txt, proc nlin, proc step | source | 6 |
| 181 | Rapid Applications Development Using the SAS System | Neil Davis | This paper discusses techniques for reducing the development time of applications, including, to the point where SAS/AF frames can be built without writing any code. This paper will also di scuss the importance of creating consistent user friendly interfaces and how this aids rapid application development. Techniques discussed will include creating sub-classes, composite widgets, and macros |
macro variable, macro facility, excel, sas base | source | 7 |
| 182 | Reading and Writing Character Data | Craig Dickstein, Marge Scerbo |
This is the information age. Client server, dynamic data exchange (DDE), object linking and embedding (OLE), and open database connectivity (ODBC) have been added to our vocabulary. Each of these allow quick access to data in a variety of formats. But with ail these advances, the need to read character data files and to create ASCII text files is still a major function in the data processing environment. The necessity to share data across platforms, operating systems, and software packages adds to the complexity of daily tasks and often the most direct solution is character data. This paper will discuss the process of reading and writing character data. Examples will be provided with each step. Beginning programmers will be able to follow the conceptual process quite well, while the more experienced analysts may gain some insight into problem solutions. So, the short and tall of this paper will include the simple and the complex | infile statement, file statement, input statement, dataset, put statement, filename statement, txt, data step, do loop, missing value, character variable, length statement, delimited file, retain | source | 8 |
| 183 | Regional Theatre: Statistical Reflections on the Bottom Line | James D. Ryan | The purpose of this paper is to paint a statistical portrait of the current economic state of regional theatre in the United States. How have regional theatre companies fared during the 1980's and into the 90's? As a result of rising production costs, increased competition for audience, and widely acknowledged diminishing federal support, are these theatres now subject to the same financial strains as Broadway theatre? This study uses the SAS System to reveal trends in the bottom line in the state of representative regional theatre. In particular, PROC PLOT, PROC CORR, PROC MEANS and PROC REG are used to identify and test for the significance of trends in regional theatre in the 1980's and 1990's. The author concludes with comments on the ease of learning and using the SAS System |
anova, response variable, proc step, estimate, proc reg | source | 7 |
| 184 | Repeated Measures Analysis with Discrete Data Using the SAS System | Gordon Johnston, Maura E. Stokes |
The analysis of correlated data arising from repeated measurements when the measurements are assumed to be multivariate normal has been studied exten- sively. In many practical problems, however, the normality assumption is not reasonable. When the responses are discrete and correlated, for example, different methodology must be used in the analysis of the data. Generalized Estimating Equations (GEEs) provide a practical method with reasonable statistical efficiency to analyze such data. This paper provides an overview of the use of GEEs in the analysis of correlated data using the SAS System. Emphasis is placed on discrete correlated data, since this is an area of great practical interest | source | 6 | |
| 185 | Report Writing, SAS/GRAPH Creation, and Output Verification Using SAS/ASSIST Software | Matthew J. Becker | Since the release of SAS/ASSIST, SAS has given users more flexibility in the routine generation of SAS output, including graphs. Novice users can now "point-and-click" their way to table and graph generation. In addition, the code generated by the user's selections is constructed and provided in the SAS Log. If desired, this code can be copied into a program for future submissions. Generating SAS/ASSIST output is also beneficial in verifying table output generated from a SAS program. A user may use a combination of SAS data summarization procedures and a Data _NULL_ to generate a listing of the summarized data. They can then use SAS/ASSIST to generate a PROC TABULATE of the data and verify that their output is correct |
proc step, proc print, adverse events, bar chart, horizontal bar chart, proc tabulate, class variable, data cleaning | source | 6 |
| 186 | Reports Based on SAS Output: Taking Advantage of PROC PRINTTO, DATA Steps and PROC GPRINT | Lauren E. Haworth | The SAS@ System is a powerful tool for data manipulation and analysis, but it often produces far more output than you want to read or report. Instead of scanning through a lengthy log printout looking for error and warning messages, or hand copying a few dozen figures into a table from a hundred-page output printout, let SAS do the work. This paper introduces a variety of time-saving techniques for producing concise summary reports. The key is using the PRINTTO procedure to direct procedure output to log and print files. These files are then available to the DATA STEP for further refinement or analysis of the results. For example, by using a DATA STEP to review the SAS log, you can create self-monitoring production jobs that print error reports when warranted. By using a DATA STEP to review a lengthy output file, key |
proc step, proc printto, by group processing, sas output, proc glm, proc print, standard deviation, correlation, proc genmod, error message, txt, sas log, excel | source | 9 |
| 187 | Resolving and Using &&VAR&I Macro Variables | Arthur L. Carpenter | One of the most important aspects of the Macro SAS code is parsed, the macro variable can be Language within the SAS System is its ability used to store snippets of code, variable names, to create code dynamically. This allows the constants, or even pieces of variable names. developer to write code that will do a series of These macro variables can then be joined operations without knowing exactly what those together to form new and exciting combinations. operations will be at execution time. When macro variables contain the name of This presentation will show how double other macro variables the resulting code will ampersand macro variables are resolved and how often contain two (or more!!) ampersands. The compound macro variables can be used to create following sections address the issue of making dynamic code. Examples include using a list in a sense of macro variables with multiple flat file to create a set of macro variables that ampersands. control a series of events | macro variable, proc step, flat file, macro definition, macro loop, %if-%then-%else | source | 4 |
| 188 | Response Surface Optimization Using JMP Software | Melvin T. Alexander | contour plot, main effect, response variable | source | 8 | |
| 189 | Round Pegs Into Square Holes: Data Warehouses for the Hardware Impaired | Michael L. Davis | One of the dirty secrets of most data warehouse projects is that they require vast amounts of disk drive space and robust computers for successful implementation. Unfortunately, not every organization that lusts for a comprehensive data warehouse can finance the tab for the hardware that may be required to create the warehouse of their vision. Bassett Consulting Services has helped two clients make better use of limited computing resources through a two step approach. First, an active data dictionary permits "point and click" selection, renaming, joining, and sub-setting of data, even when some of the elements reside on tape cartridges or in hierarchical files. Then "code engines" create SAS code on the fly to extract the requested data from their actual physical locations and transform the data into SAS data sets. These data sets even contain variable labels and formats, courtesy of the data dictionary, and are ready for further analytical processing | data dictionary, dataset, variable list, data step, input statement, catalog entry, variable, set statement, label statement, excel | source | 6 |
| 190 | Running Multiple SAS/AF Applications in a Single SAS System Session | Mark L. Schneider | For years internal users of Institute tools have been struggling with the startup time attributable to an interactive SAS session. Since more and more SAS applications are being developed by departments like MIS, Development Support, QA, and Professional Services, invoking the various SAS sessions is not only time-consuming, but a growing resource crunch as well. The MULTISAS project attempts to address this problem by providing a framework and set of standards for multiple SAS/AF applications to coexist within a single SAS session. Pertinent issues include user profiles, temporary data sets, global macro variables and macro routines, librefs/filerefs, formats, global SCL lists, options, window names, and interapplication communication. By sharing a single SAS session, applications require less memory and launch in a fraction of the time than they would in a more stand-alone form |
libname statement, macro variable | source | 6 |
| 191 | SAS Code Generator Based on Table-Driven Methodology in a Batch Environment | Arthur K. Yao | The main objective of the Table-driven System is to build a reliable batch application that is easy to develop and maintain. Most batch programs are treated as a black box with long lines of repetitive code that is very difficult to maintain. The Table-driven system will allow subject matter specialist to easily change system variables and values without requiring code changes. The type of batch applications, that the Table-driven System is best suited, are applications that have simple repetitive logic with different input parameters. The Table-driven System consists of three main components: a conceptual table (Edit Table), a corresponding macro code to support the conceptual table (Edit Macro), and the Code Generator Macro to piece it all together in a SAS@ DATA STEP. The Edit Table consists of Business Rules, and each Edit Table requires a corresponding Edit Macro to translate the business rules into SAS code |
macro variable, data validation rules, dataset, macro definition, imputation, numeric variable, sas log, variable list, txt, excel, data step, macro loop | source | 6 |
| 192 | SAS Data Views: A Virtual View of Data | John C. Boling | The concept of a SAS data set has been extended or broadened in Version 6 of the SAS System. Two SAS file structures now function as SAS data sets: SAS data files and SAS data views. Both file structures can be processed as SAS data sets in DATA steps or PROC or procedure steps. This paper introduces the concept of a SAS data view, presents its advantages and disadvantages, discusses the three types of SAS data views, and compares its structure with that of a SAS data file. Defining a SAS Data View The SAS data file is already familiar to experienced SAS users because it represents what, historically, has been called a SAS data set. For example, 1982 Version SAS data sets and Version 5 SAS data sets are technically referred to now as SAS data files. This is essentially a change in terminology. The new file structure and definition in Version 6 is the SAS data view. Unlike SAS data files, SAS data views do not contain actual data |
dataset, proc sql, proc step, proc print, create view, proc contents | source | 5 |
| 193 | SAS Interface for Run-to-Run Batch Process Monitoring Using Real-time Data | Todd R. Nelson, Scott D. Grimshaw |
The statistical metho ds for statistical pro cess con/- trol using real/-time data in batc h pro cesses require in tensiv e computation on large amoun ts of data/. The real/-time data from a batc h pro cess consists of frequen t measuremen ts on sev eral di/#0Beren tv ari/- ables during the batc h op eration time/. In the ex/- ample in this pap er/, /5/8/8 measuremen ts are tak en on elev en di/#0Beren tv ariables during a single batc h run/. Using SAS/#2FAF | source | 5 | |
| 194 | SAS MACROS: A Gentle Introduction for the Fearful | Ralph W. Leighton | macro loop, macro variable, where statement, calendar year, macro definition, dataset, %if-%then-%else, proc print, proc step, call symput, macro facility | source | 6 | |
| 195 | SAS Program Efficiency for Beginners | Bruce F. Gilsen | dataset, where statement, if-then-else, proc step, character variable, subsetting if, conditional do loop, input statement, proc append, set statement, numeric variable, sas function, put statement, flat file, missing value | source | 10 | |
| 196 | SAS Software Distribution Issues - An Academic Perspective | Gerardette M. Furlow | The SAS software consultant for a university is often faced with the tremendous task of distributing the SAS System to faculty, staff, and students of the university. These faculty, staff, and students generally request the SAS System for a variety of operating systems. As the SAS System continues to grow, the SAS software consultant must decide which software distribution methods will work the best in a heterogeneous environment. This paper will review the methods used by the North Carolina State University (NCSU) Computing Center (CC) to distribute the SAS System to campus users | grid computing, order by | source | 3 |
| 197 | SAS/ASSIST Software for Beginners | Sally M. Muller, Arturo Barrios |
Four years ago we began teaching a two-hour | dataset, flat file, where statement, sas library, proc step, catalog, data step, input statement, sas output, libname statement, character variable, sas programming, proc freq | source | 14 |
| 198 | SAS/GRAPH Blues? SAS/FRAME to the Rescue! | Kathy Shelley | This paper shows how SAS/FRAME can be used to automate repetitive graph production, thus enabling users to produce well-designed graphs without writing |
sample, bar chart, proc step, regression analysis, proc reg, anova | source | 6 |
| 199 | SAS/INSIGHT Software or JMP Software: A Comparison | Andy Mauromoustakos | At the University of Arkansas in the Dale Bumpers College of Agricultural, Food and Life Sciences the Agricultural Statistics Laboratory is responsible for teaching every year "service courses" on Statistical Methods, Experimental Designs, and Applied Regression. In the past couple of years, we have experimented using SAS/INSIGHT and JMP as the tool kits for carrying out the analysis covered in these courses. In this paper we are going to concentrate on the advantages and disadvantages of each in carrying out analysis, gaining insight in terms of the models being fitted and understanding better the results of the fit. We have found that both SAS/INSIGHT and JMP were excellent exploratory and analytical tools. They both helped students discover more, interact more and understand more as compared to previous years when students only used SAS |
proc glm, proc mixed, regression analysis, repeated measures, repeated measures anova, likelihood function, proc nlin, proc genmod, proc step, proc princomp | source | 3 |
| 200 | SAS/SPECTRAVIEW Software and Data Mining: A Case Study | Ronald E. Stogner, Aaron Hill |
Advances in information technology are allowing organizations to collect and store larger amounts of detailed data. Today's challenge is for companies to turn this information into a competitive advantage. Application areas, such as data mining, database marketing and decision support, hold the promise of turning this information into profits. One key component to this process is data visualization. This paper presents a practical example of using data visualization technology to assist companies in the decision support process. SAS/SPECTRAVIEW software is used to spot key relationships and trends in a large data set. SAS/SPECTRAVIEW Software and Data Mining Major companies today are faced with a growing dilemma. They have amassed large quantities of data related to their businesses and their customers. The challenge for these companies is to turn this data into profitable information |
data mining, predictor variable, sample, bar chart, response variable | source | 5 |
| 201 | SAS/Warehouse Administrator Usage and Enhancements | Terry L. Lewis | data mart, proc step, data warehouse, dataset, proc sql, catalog, macro variable | source | ||
| 202 | Setting Dates In a Production Job | Deb Cassidy | A set of production jobs produced several reports. The original code required a programmer to edit several jobs each month to speci~ the correct fiscal years and month for the report. Editing this monthly job required considerable time and was very prone to errors. There were numerous occurrences where the value of a variable or the variable name had to represent a specific fiscal year or a month. For example, some reports needed values for a variable to be 'FY96' or FY95'. Others needed variables named Ju195 and Ju196. Titles were required that read "FY 96 vs. 95" or "Summary for March 96". This paper shows how to use date functions and macros to set all these values without editing a single job | macro variable, if-then-else, calendar year, data cleaning | source | 4 |
| 203 | Skipping, The Easy Way | Janet E. Stuelpner | The testing has begun. In order to see if the different parts of your SAS(@) program are working, you need to use PROC PRINT or some other procedure to output the data quite often. You practically have one after each DATA STEP or PROC STEP. What a pain in the neck it is to pull them all out when your testing is done and the program is perfect. Well, now you don't have to do it. A simple little macro will allow you to leave the source code there. Another great use for this macro is to comment out many lines of code where documentation is plentiful. Sometimes it is difficult to remove sections of code with standard comments, where there are comments that exist . Read on to find out an easy way to skip over code with Yoskip |
proc step, proc print | source | 2 |
| 204 | Some Practical Ways to Use the New SAS Pattern-Matching Functions | Michael D. Rhoads | The 6.11 and 6.09E releases of SAS software contain, in experimental form, a powerful new set of pattern- matching functions, which can be used in DATA steps, macros, or SCL code. This paper provides a summary description of these new routines and includes several examples of how their use can significantly reduce the coding effort required to perform common tasks | numeric variable, sas base | source | 4 |
| 205 | Some Tips and Examples for Using SAS PROC TABULATE | Pei Lee Tien, Tsung-Hua Lin, Mike McGranaghan |
proc step, proc tabulate, proc univariate, proc means | source | ||
| 206 | Statistical Enhancements in Release 6.12 of the SAS System | Maura E. Stokes | Release 6.12 of the SAS System brings several key enhancements to SAS/STAT software. Generalized Estimating Equations (GEE) methodology, a popu- lar technique for the modeling of correlated response data, has been incorporated into the GENMOD proce- dure. Another key update is the computation of exact p -values for a number of statistical tests provided by the FREQ procedure. In addition, this paper provides an overview of enhancements to the MULTTEST, MIXED, GLM, and NPAR1WAY procedures. GEE Methods in the GENMOD Procedure GEEs were introduced by Liang and Zeger (1986) as a method of dealing with correlated data when, except for the correlation among responses, the data can be modeled as a generalized linear model. Correlated data can arise from situations such as /#0F longitudinal studies, in which multiple measure- ments are taken on the same subject at dif- ferent points in time |
source | 7 | |
| 207 | Statistical Methods for Reliability Data Using SAS Software | William Q. Meeker, Luis A. Escobar |
In the past decade there has b een a high degree of in terest in impro ving the qualit y /, pro ductivit y /, and reliabilit y of man ufactured pro ducts/. Global comp etition and higher customer exp ectations for safe/, reliable pro ducts are driving this in terest/. After the areas of exp erimen tal design and statis/- tical pro cess con trol the one of reliabilit y is the next to receiv e a high degree of emphasis/. Indus/- try/'s curren t concern is on ho wt o m o v e rapidly from pro duct conceptualization to a cost/-e/#0Bectiv e highly reliable pro duct/. P art of the reliabili t y assurance pro cess requires conducting tests and studies to obtain reliabilit y data and to turn these data in to useful information for making decisions/. In this pap er w e consider the use of mo dern metho ds for analyzing time/-to/-failure data that can b e implemen ted using SAS soft w are/ | cumulative frequency, probability distribution | source | 10 |
| 208 | Storage Strategies for Data, Formats, Catalogs and Other Information in Application Development Using The SAS System | Sharon Mosley-Hixon, Raymond L. Ransom |
When doing cross-platform development using the SAS System, developers have many options for the storage and access of information needed and generated by their applications. Using the many different engines provided and SAS/ACCESS@ software, developers are not restricted to traditional SAS table and catalog storage. Alternative means of storage can enhance an application by minimizing maintenance required, increasing query speeds for large tables, standardizing storage strategies, efficiently using RAM, and utilizing the advantages of the Structured Query Language (SQL). Developers of a sexually transmitted disease (STD) information system (STDINFO) at the Centers for Disease Control and Prevention(CDC) tried storing information in several standard and alternative structures recognizing benefits and short-comings of each approach |
dataset, proc sql | source | 4 |
| 209 | Structuring Your Data Warehousing Project: Moving from the Concept to the Reality | Peter R. Welbrock | For every successful Data Warehousing project, there are many that fall by the wayside; ignored, forgotten or scrapped. Although just a continuation of the familiar I.T. pattern, these failures represent a fundamental misunderstanding of Data Warehousing and should be treated as such. This paper is intended to focus on the process of Data Warehousing, discussing specifically the importance of a structured transition from a specific concept to reality of implementation. This paper will purport the view that Data Warehousing projects often fail due to the lack of understanding of this transition, either due to it being ignored, or due to ignorance of its existence | data validation rules, data mart | source | 8 |
| 210 | Subclassing the FRAME Class to Incorporate Documentation Templates and Standard Widgets | Mark Bodt | When a new FRAME entry is created using the build window, SAS@ uses the FRAME class that is provided with SA.'YAF software. Standardizing the look and feeI of an SAS/AF application is one factor that determines how intuitive an application is. Frames often have common components such as OK, Cancel, Help buttons etc. The layout and positioning of these is important to ensure uniformity across different screens of an application. Features of SAS/AF release 6.11 (aka Orlando) promote Object Oriented Application Design and allow developers to develop their own classes to ensure that visual standards are easily incorporated into an application. The SAWAF FRAME class is one object that can be subclasses to aid developing applications that have a uniform look & feel. This paper will discuss the subclassing of the FRAME class, working through an example whereon creating a new frame entry, the type of FRAME (eg dialog box) and the population of widgets in the FRAME will be demonstrated |
character functions, catalog entry | source | 6 |
| 211 | Successful Business Intelligence Systems: Improving Information Quality with the SAS System | W. Droogendyk, L. M. Harschnitz |
business intelligence, data governance, data integrity, data validation rules, data cleaning | source | 6 | |
| 212 | Summarizing Impossibly Large SAS Data Sets for the Data Warehouse Server Using Horizontal Summarization | Michael A. Raithel | Data warehouse applications thrive on pre-summarized data. When a warehouse's data originates on a mainframe computer, The summarization that PROC SUMMARY traditionally it makes sense to take advantage of the mainframe's power to executes can be thought of as "vertical summarization". It is summarize the data before porting it to the warehouse server. "vertical" b ecause the SUMMARY procedure builds a vertical The SAS System is the perfect tool to use to summarize data matrix in memory of the different levels/values of the class bound for a data warehouse. However, summarizing very variables. For example, consider the following code: large SAS data sets with many CLASS variables can be problematic even on a mainframe computer. PROC SUMMARY data=cdsales; This paper introduces the concept of Horizontal var salesamt; Summarization |
dataset, class variable, proc means, batch job, proc step | source | 5 |
| 213 | Survival Strategies and Solutions for the New Millennium - Year 2000 | Kirk Paul Lafler, Sunil Kumar Gupta, Charles E. Shipp |
As the turn of the century approaches, critical challenges face organizations world-wide. Will mission-critical computer applications be equipped to handle the numerous calculations and comparisons required by businesses to successfully operate? And how can organizations smoothly transition into the next century without impacting current operations and staffing levels? If estimates are accurate, as much as 90 percent of all business applications will be impacted in some way by the coming millennium. A successful strategy is needed to ensure cost-effective, timely, and lasting solutions | sas programming, sysdate9 | source | 5 |
| 214 | Systems Architecture Solutions for an STD Information System | Keith Humphrey, Raymond L. Ransom |
The Division of Sexually Transmitted Disease Prevention (CDC) collects data on occurrence of STD'S and disseminates this information throughout the world public health community. DSTDP downsizing and the resulting need to maximize resources are necessitating the move of programmers into application development roles. Many programmer person-hours are spent on ad hoc requests for specific subsets and basic analyses on relatively static surveillance data tables. The tables currently reside on an IBM MVS mainframe. Many epidemiological and behavioral researchers and statisticians in the Division, hereafter referred to as "users", frequently wished to query these tables, but were unfamiliar with the mainframe environment. Therefore, they would request a subset of tables to be downloaded to the SAS@ System for the Microsoft Windows@ environment | proc sql, libname statement | source | 6 |
| 215 | Taking Advantage of the SAS System on Windows NT | Mark W. Cates | Windows NT is fast becoming the universal desktop client operating system as well as an important file and compute server for mission critical applications. This paper presents a | proc sql, sql server | source | 10 |
| 216 | Ten Good Reasons to Learn SAS Software's SQL Procedure | Sigurd W. Hermansen | SAS PROC SQL works interchangeably with and complements DATA STEP programs and other procedures, but does it offer any new capabilities? Some say no. This tutorial presents a series of examples of PROC SQL solutions to problems that would prove very difficult or cumbersome to implement without SQL. Examples introduce the use of table and column aliases; catalogued views; inline views; host-variable references; summary functions applied by group; and complex joins. Practical applications of SQL constructs make a convincing case for learning these useful tools. A few examples of some DATA STEP constructs that prove difficult to match in SQL round out the discussion. ___________ During the few years since the introduction of SAS PROC SQL, the use of SQL for database access has seeped slowly into the large base of SAS programmers. Slowly, from my point of view, because I believe that PROC SQL represents a major step forward for the SAS System and that it deserves much wider use |
proc sql, proc step, having, dataset, where statement, macro variable, sas programmer, data step | source | 5 |
| 217 | The Art and Science of Biostatistical Display | Dominic T. Moore | data visualization, data science | source | 4 | |
| 218 | The Collection and Integrated Access to Network Performance Information in a Large Scale Client/Server Environment Using SAS | Tom MacFarland, Glen Bechtold |
dataset, trouble ticket | source | ||
| 219 | The Evolutionary Data Warehouse-An Object-Oriented Approach | Amy Turske McNee | This paper describes techniques for designing both the front and back end of a data warehouse in such a way that companies can continue to evolve their warehouse and query tools as their business changes, instead of continuously having to restructure and rewrite their existing tools. Object-oriented design and pattern languages are also discussed | data warehouse, data mart, where statement, proc sql | source | 6 |
| 220 | The Fast Food Approach to Data Warehouse Reporting: Using SAS/AF and FRAME to Build a Non-Technical User Interface | Grace La Torra, Esther Steiner |
create table, macro variable, proc tabulate, proc step, proc sql | source | ||
| 221 | The Fuzzy Feeling SAS Software Provides to the Electronic Matching of Records without Common Keys | Charles S. Patridge | source | 6 | ||
| 222 | The Parameters: A Statistical Methodology to Determine the Profit of Business Activities | Ursula Herr, Giovambattista Giangrieco, Fabio Zaccaria, Danilo Ballanti |
Sogei, the Agency of the Ministry of Finance for data computing, has created, within its fiscal matters research program, a system of parameters to determine the profits, the compensations, and the volume of business made by companies, and individual in business. The parameters (also known as "Indexes of Profit") are based on a methodology that determines the amount of profit a person in business would be likely to make under normal market conditions. The estimation of the parameters is calculated on the basis of the income tax returns filed with the Tax Registry (Internal Revenue), by selecting, for each economic activity, a sample of tax payers who are "economically correct" based on economic conditions, and economic-accounting indexes. To construct the parameters, homogeneous groups of tax payers in the same type of business are identified | sample, cluster analysis, proc princomp, regression analysis, predictor variable | source | 3 |
| 223 | The Power of the SAS Date Functions: Creating a Utilization History for Residents of Nursing Homes | Sandra T. Rothwell, Mary Ann Bush, Ilene Gottfried, Dawn Scott |
The 1985 National Nursing Home Survey and Followup collected data on a national probability sample of 11,181 persons living in nursing homes in 1984 and 1985. For each person, data included up to 103 admission-discharge date pairs describing stays in nursing homes and hospitals. Dates were not collected in chronological order and were collected from several sources. Thousands of dates were incomplete and hundreds of reported stays conflicted with one another. The first challenge in organizing this data is making it sensible: imputing missing portions of dates, correcting conflicts, and maintaining "markers" for stays with too little information for imputation. The second challenge is presenting the data so they can be easily used for varied analyses and still account for variations in nursing home discharge policies. The task would be almost intolerable without the powerful, easy to use SAS date functions | sample, lag function | source | 7 |
| 224 | The Realities of Downsizing: Moving a SAS Application from MVS to UNIX | Kimberly J. LeBouton | Downsizing in the current business world is deemed necessary for companies to remain competitive. Companies are downsizing mainframe applications to smaller platforms in the hope of saving money and gaining productivity for both users and developers. This paper will explore the realities of downsizing an MVS SAS application to UNIX at a major manufacturing company. Managing the Project Business reasons for moving the SAS application to the UNIX platform. Key issues in planning and managing the transition. What operating system to use for UNIX emulation: Windows NT or Windows 95 ? Downsizing when the new platform is not yet in place. Convincing "mainframe dinosaurs" that UNIX is a productive world for SAS programmers. Key Technical Issues Moving 20 gigs of data across platforms on a weekly basis. Managing over 300 datasets. Converting SAS code. To conclude, a financial picture will be presented to show what gains were actually made in reducing mainframe CPU utilization | dataset, proc step | source | 11 |
| 225 | The SAS Data Warehouse, a Real World Example | Martin P. Bourque | This paper discusses building a data warehouse for the Technical Support Division at SAS Ins titute. It starts with the decision to build a data warehouse, and proceeds through the planning stage to the exploitation. It focuses on the need to be flexible at all stages, and the reality that building a data warehouse is an iterative process | data warehouse, data cleaning, star schema, capacity planning | source | 6 |
| 226 | The SAS/IntrNet Application Dispatcher | Donald J. Henderson, Edmund Burnette, Vincent DelGobbo, John Leveille |
The Application Dispatcher component of SAS/INTRNET Software allows a user to run a specified SAS Application program on demand and return the generated Internet Content to a Web Browser. The Application Dispatcher is one of the compute services of SAS/INTRNET software and is composed of the following components: 1. The Application Broker CGI The link between the Web Browser and the compute services. Resides on the Web Server and forwards requests for processing to the Application Server(s). 2. The Application Server An SCL program that listens for requests from the Dispatcher on a defined TCP/IP socket. The Application Server runs the specified SAS Application. 3. SAS Applications SAS programs that perform specified processing. They generate the results (Internet Content) which are sent back to the Web Browser by the Application Server via the Dispatcher. SAS/INTRNET software includes several Dispatcher Applications. The majority are customer supplied |
macro variable, macro definition | source | 9 |
| 227 | The Tank Battle | Judy Rosten | source | 6 | ||
| 228 | The Tobit Model: An Example of Maximum Likelihood Estimation with SAS/IML | Charles B. Hallahan | likelihood function, maximum likelihood estimation, sample, proc calis, estimate, regression analysis | source | 6 | |
| 229 | The Utter "Simplicity?" of the TABULATE Procedure - The Final Chapter? | Daniel E. Bruns | proc step, proc tabulate, label statement | source | 6 | |
| 230 | The Year 2000: Preparing for the Inevitable | Richard D. Langston, Chris Williams |
The Year 2000 represents a challenge to application developers and system programmers throughout the computing industry who rely upon dates with years represented by two digits in their applications and programs. This paper discusses various approaches to preparing your SAS applications and programs to be Year 2000 "ready" and compliant | sysdate9, date variable, options statement, sas log | source | 5 |
| 231 | To Subset or Not to Subset | Janet E. Stuelpner | Sometimes you need all the data in a data set. Sometimes you don't. When testing a program, it is better to use a subset of the data than the whole population. How can you write a program without the need to remove a bunch of code after you are finished testing? Macros are the answer. Macros can be great tools when trying to subset data. By defining three small macros at the beginning of your program ( OAiff, OAwear, %and ), very few changes need to be made to change from one subset to another. Or you can just run the entire population from the data set. This paper will show you how to do it | where statement, proc step | source | 3 |
| 232 | Tracking Air Quality Trends with SAS/GRAPH | David Mintz, Terence Fitz-Simons, Michelle Wayland |
Tracking and interpreting ambient air quality trends are pollutant". The tile map can also be used to display other the main functions of the Air Quality Tr ends Analysis temporal patterns. For example, displaying diurnal Group at EPA. SAS/GRAPH is instrumental in this patterns would work much the same way, except each tile process, allowing us to study trends using several would represent an hour of the day. Then day-to-day graphing techniques. This paper discusses graphics we tre nds, let's say for one week, could be examined by have generated using combinations of the GMAP, including multiple tile maps on the same page. The tile GCHART, and GPLOT procedures. We will show how map, if carefully constructed, can convey complicated these graphics help us to discover, and to some extent temporal patterns in an easily understood manner. explain, geographical, seasonal, and temporal patterns in the data |
box plot, bar chart | source | 6 |
| 233 | Translation Tables: Myth &Reality | Philippe Jalbert, Normand Létourneau, Dominic Roy, Jean Hardy |
In the always growing world-wide communication, ease of access to numerous databases and environments in various national languages is now fact of life. Correctness of interpretation of language specific characters is becoming a common issue in Client/Server. This paper is addressing the special characters' translation problem and suggests the SAS Translation Products as a proven effective solution to this problem. The authors are sharing their factual experience with the audience. They are demonstrating with an actual case how complex it may be and how easy it may become. In fact, they will explain why reading a file from outer source may end up at displaying many dark squares instead of readable text. The authors are not pretending to answer all the questions that may be raised in the translation world, but will guide audience toward the correct path within the SAS solution. Intended audience: SAS programmer analysts, project leaders, application developers and end users | translate, data warehouse | source | 5 |
| 234 | Two Methods to Produce Mean Plots of Clinical Trials Data: Why Simplifying with Annotate is Not an Oxymoron | Michael A. Riddle | This paper highlights a couple of strategies for using the SAS/GRAPH software to produce clinical trials graphics. Two methods of producing a simple figure of four treatment group mean values with ±95% confidence intervals are illustrated. The first method produces the graph using two plot statements on three axes and eight symbol statements. An unexpected problem with using this method is explained. The second method uses alternative code to solve this difficulty. The same figure is generated with one plot statement on two axes and only four symbols. Annotation is used to produce the confidence intervals, as well as more descriptive labels for the graph. The annotate macros provided with the SAS/GRAPH software are used to create the annotate data set used in the second method |
confidence interval, clinical trial, proc calis, proc step | source | 6 |
| 235 | Understanding Face Value - Giving Users What They Want... and Still Meeting Their Needs | Kimberly A. Foster | The purpose of this paper is to provide a general | business intelligence, data mining | source | 5 |
| 236 | UnifyPow: A SAS Macro for Sample-Size Analysis | Ralph G. O'Brien | UnifyPow is a freeware SAS macro that performs statistical power analysis and other matters related to sample-size choice. Its functionality covers an extensive set of methods. One-group tests include the t and Wilcoxon for H 0 : m = m 0 ; the binomial and Z approximation for H 0 : p = p 0 ; t and Wilcoxon for paired means; McNemar's for paired proportions; and Fishers's r-to-Z for H 0 : r = r 0 . Two-group tests include t and Wilcoxon-Mann- Whitney for H 0 : m 1 - m 2 = d 0 ; c 2 , likelihood ratio (LR), and Fisher's exact for H 0 : p 1 = p 2 (association in 2 · 2 tables); r-to-Z for H 0 : r 1 = r 2 . J-group tests include ANOV A via the cell-means model with general linear contrasts; c 2 and LR tests for proportions (2 · J tables) with general linear contrasts on J logits. Also covered are the test of H 0 : b j = b j0 in a multiple regression model predicting Y from q Xs ("Y | q Xs") in which X j has tolerance Tol(X j | sample, power analysis, sample size, anova, likelihood function, regression analysis, correlation, standard deviation, logistic distribution, f-test, rank test, proc freq, binomial distribution | source | 6 |
| 237 | UNIX Large File Processing Secrets | Karsten M. Self | To most SAS programmers working in the UNIX environment, large file processing is synonymous with the historical maximum file size limit of 2 gigabytes. Though this is a significant concern, there are additional dimensions to managing and working with large quantities of data. Large file processing is any job large enough that you think twice before typing submit. The term is applied here to any situation where a task is constrained by physical resources, including: system file size limits, system storage or workspace limits, total processing time, CPU availability, and process contention with other users. The weapons which can be applied to these are programmer time and skill. Ultimately, pushing the limits of the envelope is a question of balancing these factors. This paper identifies several techniques for large file processing on Unix, including: Recent SAS and OS large file support enhancements. Efficiency techniques. * Sorting data | cpu time, sas programmer | source | 8 |
| 238 | Use of PROC MIXED in the Analysis of Repeated Measures Data from a Clinical Trial in Obsessive Compulsive Disorder | William Bushnell, Martin Steiner |
The subject of this paper is the analysis of data from a randomized, parallel group, multicenter clinical trial in patients with Obsessive Compulsive Disorder (OCD). The purpose of the study was to evaluate the efficacy and safety of three dose levels of Paxil | proc mixed, covariance, proc step, dose, regression analysis, repeated measures anova, anova, change from baseline, covariance structure, repeated measures, correlation, likelihood function, clinical trial, unstructured covariance | source | 6 |
| 239 | Use of SAS/AF and the SAS/GRAPH Output Class Object to Develop Applications That Can Return Scatterplot Information | Michael Hartman | In today's time of 'interactive' analyses, users expect to be able to select data points of a graphic and obtain detailed information about a selected observation. SAS/AF Frame objects exist (e.g. GRAPHICS class object,) where a user can get some information about a selected observation. This class is good for basic use, but only the X and Y values can be obtained upon 'clicking' on a point and users can only get graphics within the scope of this class. For example, users can display confidence intervals, but are restricted to a 95% level. The SAS/GRAPH Output class provides a mechanism where scatterplots created using line-code SAS can be displayed but, only limited information about the spot such as SpotID, color, etc. can be obtained. This paper describes the SAS/ GRAPH scatterplot object and how to develop SAS/AF applications that allow the user to select a component/spot of any scatterplot graph and determine what part of the graph the spot is from |
confidence interval, proc sgplot | source | 5 |
| 240 | Using Dynamic Data Exchange with Microsoft Word | Jodie M. Gilmore | Dynamic Data Exchange (DDE) enables you to share data between the SAS System and many other Windows applications, including Microsoft Word. In this paper, you'll learn how to prepare your Word documents so that the SAS System can access them, and how to write SAS code that reads data from and writes data to those Word documents. Also, you'll learn how to use DDE to send commands to Word documents from your SAS session | filename statement, put statement, data step, macro facility, macro definition | source | 6 |
| 241 | Using FTP, Views, and PROC SUMMARY to Analyse Large Databases | Don Stanley | proc step, proc sql, proc means, flat file | source | 6 | |
| 242 | Using Higher Order Asymptotics to Improve P-values and Confidence Intervals Given by PROC MIXED | Ben Lyons, Dawn Peters |
P-values and confidence intervals given by the MIXED procedure are often based on asymptotic properties and may not be accurate for small sample sizes. This paper describes a simple adjustment to the signed square root of the log-likelihood ratio statistic yielding a test that can be very accurate for small samples. This adjustment, based on recent |
proc mixed, proc step, likelihood function, covariance, sample, restricted maximum likelihood, confidence interval, proc iml | source | 5 |
| 243 | Using Linear Regression and the Gibbs Sampler to Estimate the Probability of a Part Being Within Specification | Brenda Cantell | "In.]ine" or "process" specification limits are used in semiconductor processes to provide some level of assurance for product conformance that is measured at the end of wafer fabrication. However, these limits are not always set in a rigorous manner and may not prove to be an adequate in- line screening method for good and bad circuits. In this paper, an alternative way for engineers to release equipment or product for production will be explored. This approach uses a probability measure to predict how likely it is that the device will be good at functional testing based upon its in-line measured characteristic. This probability is obtained using the predictions from a linear regression equation. The Gibbs sampler is then used to construct a 100( 1-a)% credible band around the predicted probabilities. These techniques will be demonstrated using data from a semiconductor wafer anneal process | sample, estimate, proc step, posterior probability, proc iml, prediction interval, regression analysis | source | 6 |
| 244 | Using Macros to Annotate Graphs Based on Changing Data | Barry Frye, John Nelson |
Eliminating variation in the final product is one goal of a hot steel rolling mill. Normal wear of equipment occurs during the rolling process. Replacing rolling equipment while completing a customer order can introduce variation. This paper discusses one method of monitoring variation that could be introduced as a result of changing rolling equipment | proc step, sample, proc sort, macro definition | source | 5 |
| 245 | Using OOP Techniques to Make FRAME Applications More Intuitive and User Friendly | Mark Bodt | Subclassing of SAS /AF Frame objects allows developers to tailor their own classes to best suit the needs of the application. Issues that affect how intuitive and user friendly an application is will be discussed, along with some examples of subclassing that promote the usability of an application | sas output, lookup, data cleaning | source | 8 |
| 246 | Using OOP to Enhance the SAS System: An Adhoc Reporting System Using SAS Software, 3D Graphics and Web Interfaces | Charlie Bastnagel, Kevin Gates |
One of the nice features of the SAS System is that if you need functionality that is not currently provided, then using SAS (strangely enough) you can create that functionality yourself and make it appear as if it is apart of the SAS System. Such functionality as ● An Adhoc Reporting Tool that encompasses main SAS Procedures and runs in batch mode ● Structured batch submission from local clients to remote servers ● Macros that create 3D Graphics for Hbar, Vbar, Tables etc... ● Automated Remote Signon can be developed and added to the SAS System that your users use. This paper discusses the design features of the Adhoc Reporting System. In particular it focuses on the development of new software components written in the SAS AF & Macro Languages that make an object driven Adhoc Reporting System possible | proc step, macro facility | source | 6 |
| 247 | Using Resampling Techniques in PROC MULTITEST to Evaluate Surgeon SpecificResults Following Coronary Artery Bypass Graft (CABG) Surgery | Gregory L. Pearce, Peter H. Westfall |
Six surgeons perform over 800 CABG surgeries at Memorial Mission Hospital each year. Surgeon specific results are evaluated quarterly. Each surgeon is compared to the remainder of the group for seven adverse events with the intent of identifying continuous quality improvement (CQI) opportunities for clinical practice. In order to drive out fear in the CQI process, the probability of declaring a false significance must be controlled. Adjustment techniques to address the multiple comparisons problem are available (e.g. Bonferroni, Sidak) but may prove too conservative to identify CQI opportunities for the surgeons. Therefore, a | adverse events, type i error, multiplicity, proc step, significance level, correlation | source | 5 |
| 248 | Using SAS Bitwise Functions to Scramble Data Fields with Key | Sheng Luo, Xinsheng Lin |
The data modeling in banks or insurance companies often requires data files to travel from or to other companies. Some data fields, such as credit card numbers and social security numbers, while necessary to be included in the file, need to be unknown to other companies. Encryption is a way to do this by replacing original characters in the file by some other characters that make no sense. Annette I. Ladan had an excellent discussion of the keyless encryption algorithms in SAS, at the SUGI 20 Conference. This paper tries to extend the subject further to algorithms of the keyed encryption in SAS. A special effort is made to discuss bitwise operations and SAS newly added bitwise functions, as well as the pseudo bitwise operations that authors used before SAS bitwise functions came out. A sample SAS program and its result are also displayed. Although the discussion is based on | sample, credit card | source | 5 |
| 249 | Using SAS Software to Catch White Collar Criminals: A Collusion Detection System | Susan L. Schwartz, Randy Lawton |
Info Tech developed SENTRY, a Collusion Detection System, to help investigators determine the likelihood of collusive bidrigging behavior in the sealed bid marketplace. The sealed bids are used by public agencies to purchase many commodities or services. SENTRY is a PC application. Analysis takes place on the desktop, with minimal or no outside assistance from expert consultants, at least during the preliminary phase of an investigation. SENTRY was developed entirely in SAS and is available in Microsoft Windows NT and Windows 95 versions | likelihood function, batch processing | source | 7 |
| 250 | Using SAS Software to Compare Strings of VOLSERS in a JCL Job and a TSO CLIST | Randall M. Nichols | The TRANSLATE function of SAS can be used to strip out punctuation and other unwanted characters resulting in a string of words separated by blanks which can then be compared word by word. This process is generally considered a word processing function and at first might not seem relevant or appropriate to working with JCL, SYSLOGS, CLISTS, or other system related files and records. Nevertheless, these types of files and records can be visualized as a series of words rather than individual bytes. The third generation language model would be to do a byte by byte comparison, build tables, make comparisons, keep or reject, write the record. Although SAS can be used to do a byte by byte comparison, it also allows us to consider a different solution that in fact might be A solution was to write a SAS program to more intuitive and easy to code. read the FDR JCL and the TSO CLIST, | translate, index, proc sort, proc step | source | 6 |
| 251 | Using SAS Software to Compute Variances for Poisson Samples | Terry L. Pennington | Poisson sampling is a method of unequal probability sampling in which each sample unit is selected independently. It is a sample design common for economic surveys at the Bureau of the Census. Such sample designs offer increased sampling efficiency compared to stratified where equal-probability sampling. This paper discusses the module for calculating sampling variances for Poisson W = the adjusted sample weight sampling. The module is a component of the standardized X = the data value for observation I economic processing system that is currently being developed at the Census Bureau. This SAS-based system An alternative estimator is will process and tabulate survey data. Design-specific variances are then calculated for the various survey data. The SAS code for the Poisson-variance module is displayed and discussed in detail | macro definition, sample, macro loop, poisson distribution, proc calis, macro variable, dataset | source | 6 |
| 252 | Using SAS with Oracle to Add a Replica of a Large Operational Database to a Data Warehouse | Clive Cooper, Clare Somerville |
In 1995 the New Zealand Department of Social Welfare began the implementation of a large data warehouse on a UNIX platform. One of the major components in the warehouse was to be the replication of a 60 gigabyte database from Unisys DMS II into Oracle . SAS software played a pivotal role in the project. SAS provided the tools first to explore and scrub the data, then to automate the process of producing data definition macros and other files for various aspects of the systems software, and finally to maintain the Oracle database using SAS/ACCESS features. This paper covers the topics that needed to be addressed to create and then maintain the operational database replication up to date |
dataset, oracle, flat file, proc step, proc sql, cpu time | source | 7 |
| 253 | Using SAS/ACCESS Views to Retrieve DBMS Tables | Tischa A. Agnessi | A tutorial approach will be used to illustrate how useful SAS/ACCESS views can be in an environment with many types of frequently accessed data sources. Views can be consid- ered to be virtual data sets. They require mini- mal storage and can be used to obtain up-to- date results as well as to create permanent SAS data sets. Prior to accessing an existing Database Man- agement System (DBMS) table, two descriptor files must be created to define a SAS/ACCESS view of the DBMS table. Special emphasis will be placed on building the Access Descrip- tor and the View Descriptor using the ACCESS windows of the Display Manager. By using the ACCESS windows as a building block, it requires no knowledge of the SQL language syntax, and requires minimal typing. We will also examine the use of the WHERE clause and how it increases efficiency and low- ers cost |
where statement, dataset, view | source | 5 |
| 254 | Using SAS/AF as a Front End for Developing Report Program Skeletons | Jeff Hamilton, Jennifer Lester |
With the growing demands being placed on information system departments, the opportunity to off load "simple" programming tasks to non-SAS programmers adds efficiencies into the program development life cycle. Using a SAS/AF application as a front-end entry tool can build such efficiencies into program development. Standardized reporting tools developed at STATPROBE, Inc. have been designed to allow the programmer to make table shell modifications very easily. These modifications have been automated via SAS/AF allowing a non-SAS programmer to create table shells with minimal involvement of the programming staff. Standard report program "skeletons" are created by the user through AF Frames. Essential program modules are then combined to create usable SAS code. The SAS program created using SAS/AF produces a table shell which can later be modified by a SAS programmer to populate the table shell |
sas programmer, study day, dataset, macro definition | source | 4 |
| 255 | Using SAS/AF for Managing Clinical Data | Carl R. Haske | Using SAS/AF as a software development platform permits rapid applications development. SAS supplies several classes of objects that the developer can use to quickly prototype and implement systems. However, in developing applications for use in the pharmaceutical industry, it is useful to augment these classes with additional classes that provide robust data management and reporting capabilities. Classes that provide generic tools to subset data, browse data, move data, and report data are useful in the clinical research environment. STATPROBE, Inc., has developed an integrated data management system, using SAS/AF as the platform. The system incorporates security and tools that assist the valid production and analysis of the clinical data. Various modules in the system support numerous clinical data management activities. Data at the quality assurance stage is accessible remotely via the STATPROBE Data Access System |
clinical data, clinical database, data governance, quality assurance, proc step | source | 6 |
| 256 | Using Survey Data: Tips to Pick Up Speed on the Road to Analysis | Cynthia L. Williamson, Suzanne D. Kreutzer |
In this paper, we offer tips to help SAS@ programmers get to know their survey data, thereby ensuring that the road to analysis is smooth. We will address techniques to prepare for a survey, track questionnaire returns, ensure accurate data input, check for data quality, and create a data analysis file | proc step, sysrc, sample, proc compare, proc freq, proc sort, dataset, missing value | source | 6 |
| 257 | Using the SAS System for Large Volume HTML Document Production | Paul E. Pope | * Ease of Document Production and Maintenance . Documents on the World Wide Web (Web) are formatted using Hypertext Markup Language (HTML) . Formatting1 large numbers of documents can be tedious and time- consuming. However, if the documents have similar content then a simple SAS programming solution can reduce the drudgery of HTML formatting. This paper describes a SAS application that produced a large number of static HTML 2 documents for distribution on the Web | dataset, web service | source | 6 |
| 258 | Using the SAS System Release 6.12 on Windows | Gary Mehler | Release 6.12 of the SAS System for Per- sonal Computers provides support for Mi- crosoft Windows (version 3.1 using Win32s technology, Windows 95, Windows NT), and | dataset, put statement, sas base | source | 9 |
| 259 | Utilizing Clinical SAS Report Templates | Sunil Kumar Gupta | SAS programmers often have the responsibility of supporting the reporting needs of the Clinical Affairs Department of Pharmaceutical Companies. This involves generating a variety of reports to fulfill the regulatory requirements of the clinical investigation of the medical device. By establishing clinical reporting templates for each of the functional aspects of Clinical Data Management, the SAS programmer can dramatically improve the efficiency of developing and generating reports. Examples of these functional reports include patient listings, patient x-ray logs, monitor site visits, monthly status reports, & reports necessary for pre market approval application. Each type of report requires different layouts due to the different | sas programmer, sample, proc step, proc report | source | 5 |
| 260 | Validation and SAS Programming: Benefits of Using the System Life Cycle Method | Russell Newhouse | data cleaning, vital signs | source | 5 | |
| 261 | Visual Hypothesis Testing with Confidence Intervals | Robert W. Smith | confidence interval, null hypothesis, sample, degrees of freedom, sample size, hypothesis testing, proc calis | source | ||
| 262 | Want Quick Results? An Introduction to SAS/GRAPH Software | Arthur L. Carpenter | SAS/GRAPH software contains the tools and flexibility to produce high-resolution presentation quality graphs. With this flexibility comes a complexity that often discourages a new user from taking the plunge and learning SAS/GRAPH. Learning and using SAS/GRAPH does not need to be difficult. Nor are the more complex aspects of SAS/GRAPH always needed to produce graphic output that is just what your boss wants. This workshop will introduce three of the primary procedures used by SAS/GRAPH, and introduce the options and statements that make them special. We will start with TITLEs and FOOTNOTEs. PROC GPLOT will be used to create a scatterplot which will be enhanced with SYMBOL statements and a number of options. Several variations of GCHART will be demonstrated and the creation of title slides using GSLIDE will be discussed briefly. Options specific to SAS/GRAPH and how and when they should be used will be handled with an |
proc step, proc gplot, proc gchart, histogram, proc freq, options statement | source | 6 |
| 263 | Ways of Learning: What the Trainer and the Student Need to Know about Learning Styles | Judy Loren | proc step, proc print | source | 9 | |
| 264 | Web Compatible SAS/GRAPH Output the Easy Way | Ahsan Ullah | This paper describes some concepts and analyses required to create SAS/GRAPH images for use in WEB pages. It deals with an automated SAS/AF Frame system des igned to create and print a number of graphs and produce suitable graph image files for inclusion on WEB pages. Topics discussed include drill-down design, programming techniques for creating GIF files, and the creation of custom SAS Device Drivers |
source | 4 |
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