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MWSUG 1996 Papers - Index

44 papers. Source: MWSUG (Midwest SAS Users Group) conference proceedings.

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1 "How Does Your Data Compare?" 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 controlJed 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 new data prior to updating the master. thereby identifying possible bad data in the new data set proc compare, proc step, master data management, dataset, data cleaning, sample, proc print 7
2 A Macro to Estimate Morbidity Indices Laurel A. Panser,
Janice R. Offord,
James M. Naessens,
Mary E. Campion,
Sherine E. Gabriel		 In the 199Os, health care systems are under great pressure to reduce costs, to demonstrate the effectiveness of treatments, and to introduce useful reform. Consequently, health systems are being compared. These comparisons need to fairly reflect the variability in disease burden among populations. Populations with greater disease burden not only use more resources (for example, hospitalizations are longer) but have worse health outcomes (for example, mortality rates are higher). Thus, health systems serving patients with a greater disease burden will appear to perform worse than those serving a healthier clientele. These issues also apply when examining the practice patterns of individual physicians. Differences in disease burden must be adjusted (confounding minimized) to make balanced comparisons, but limited software has been available to measure disease burden medical history, proc freq, correlation 8
3 A SAS Macro For Modified Kaplan-Meier Estimates with Time Dependent Covariates Lonni R. Schultz,
Gordon R. Jacobsen,
Edward L. Petersen		 proc phreg, regression analysis 6
4 A Set of SAS Macros for Producing Statistical Reports Greg A. Grandits Monitoring clinical trials requires periodic generation of statistical reports of comparison between treatment groups. These reports usually include summary statistics for each treatment group and an assessment of statistical significance (p-values). Existing SAS procedures such as PROC TABULATE are adequate to produce a report with some summary statistics (COlUtts, means, SO, etc.), but are not adequate for other statistics (relative risks, regression coefficients, etc) or for including p-values. TL paper describes a set of macros that produce statistical reports which allows free placement of text and statistical summaries including p-values onto the report page. The user first defines columns and column widths across the report page. Text or data values (summary statistics) are then moved to these columns and specified lines using macros MOVE and NMOVE dataset, proc means, response variable, variable list, predictor variable, regression analysis, proc step, relative risk, proc genmod, class variable, clinical trial, least squares mean, anova 10
5 Advanced Uses of SAS Formats Howard Levine This paper will show how to use SAS formats for grouping observations and performing table lookups. It will also show how to use informats for redefining input values. There will be a brief overview of SAS formats and PROC FORMAT. Then the advanced topics will be explored. Additional items covered will be picture formats, permanent format libraries, and using SAS data sets in conjunction with PROC FORMAT proc format, proc step, format statement, dataset, lookup, char., proc freq 10
6 An OO Approach to Implementing Drag-and-Drop Functionality in FRAME Application Mark Olson if-then-else, dataset 7
7 Answers to Commonly Asked Statistical Questions - June 1996 Edition Mike Stockstill The purpose of this paper is to address some common 'how to" and 'what does lhis mean" users' questions collected by 1he statistk:s group in Technical Support. Product discussion inctudes SAS/IML, SASIINSIGHT, SAS/STAT, SASJOR, SASlQC, SASfETS. SASJLAB, JMP, and base SAS software. The emphasis is on what can be done with lhe current releases ralher lhan with future releases, although comments are provided where appropriate. Understanding 1he paper requires lllUe or no technical or statistical expertise. The paper should be particularly useful to Site representatives whO face a lot of questions abOut statl$tlcs. The paper itself is based on our intemal notes to each o1her and is not really intended to stand alone as any sort of documentallon. We all contribute, the informallon is constanlly updated, and we use this Information to help resolve as many calls as possible on initial contact 11
8 Applying Generalized Linear Models to Discrete Response Data Using the SAS System Maura E. Stokes This tutorial discusses fitting regression models to discrete data within the framework of generalized linear models. Response data includes binomial, multinomial, and count. Logistic and probit models are applied to binomial data, polytomous and cumulative logit models are applied to multinomial data, and Poisson regression is applied to count data. Parameter estimation, model building, modee1 checking, and statistical inference are discussed for applications of these various models. Overdispersion for binomial and Poisson data is discussed, and various measures for correction are introduced, including using the log-linked negative binomial regression for overdispersion count data. Participants will learn to choose the appropriate SAS procedures to fit a particular discrete response model, as well as learn the basic syntax, default output and some useful options of these procedures. They will receive a copy of the overhead transparencies at the tutorial. 205 Outline binomial distribution, logistic regression, poisson distribution, regression analysis 2
9 Are you FUNCTIONally Literate? Allan M. Kominek This tutorial will consider a number of SAS functions and the many ways that they can be used to make the life of your friendly. neighborhood SAS programmer a little easier sysdate9, sas function, input statement, date variable, substr function, character functions, numeric functions 6
10 Building Efficient Data Warehouses: Understanding the Issues of Data Summarization and Partitioning Susan Tideman,
Robert Chu		 An effk:Ient data warehouse enab/e$ better and fastIIr decisions. To biJjJd an efficient data warenouse. you neeI1lO knOW how best 10 summarize data and how best 10 partition the summarized data warehouse, proc means, data mining, train-test split 8
11 Clinical Data Management Using SAS/AF Carl R. Haske Using SASlAF 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, when developing applications for use in the pharmaceutical industry, it is useful to augment these classes with acidltlonal 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. 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 data governance, dataset, clinical data, clinical database, audit trail, quality assurance, clinical data management, proc step 8
12 Creating and Linking Customized SCL Objects Andrew A. Norton relational database, bar chart 6
13 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. This tutorial will demonstrate how to create templates using the GREPLAY procedure either interac tively 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 5
14 Customized Report Writing Using PROC PRINTO Kim L. Kolbe Ritzow This paper will show how to take select information from the various SAS procedure's output Oike PROe FREQ, PROe TABULATE, etc.) and combine the information into a single ·customized· report by using PROe PRINTTO to capture the procedural output, the DATA STEP to read in the external flat file that PROe PRINTTO creates, and the various DATA STEP tricks and techniques used to put the information back together Into a single ·customized" report proc step, macro variable, flat file, proc printto, _eof_, dataset, proc freq, sample 12
15 Data Warehousing and Data Marts: The Who, What, Where & Why of Accessing Critical Data Becky Brown Users are relying on computers to help them become more self-sufficient in getting their job done. They want to extract information from the company's enterprise systems with minimum interVention from the Information Systems (IS) staff. The solution to empowering these users and eliminating the impact on your enterprise databases is to provide them with access to a separate data repository of information to use for business intelligence purposes. This paper examines the role of the SAS System. specifically SAS/ACCESS software and SAS/CONNECT software. in building a data warehouse of decision support information in a client/server environment 11
16 Detecting Changes in Mean of Correlated Data Tze-San Lee,
Lei Zhang		 likelihood function, nonparametric test, maximum likelihood estimation, time series analysis, traffic data 4
17 Developing Process Flow Diagrams with SAS 6.11 Roderick Lashley 3
18 Effective Presentations - A Bad Example Deb Cassidy Effective Presentations - A Bad Example Deb Cassidy, Cardinal Health Inc. Does this title leave you wondering if this will really be a bad presentation as in 'unfavorable' or an 'excellent' presentation and I'm using the word 'bad' as slang for 'good'? This paper win not be presented in the traditional fonnat. All of you could simply read the conference proceedings to know your visual aides must be a minimum size, you shouldn't use slang and other helpful hints. As a Section Chair last year, I started noticing patterns in the evaluations and decided to give this presentation. I will give a short presentation and then there will be AUDIENCE PARTICIPATION. I will intentionally give a 'bad' presentation and you get to tell me the 'unfavorable' or 'excellent' reasons why it was 'bad'. Obviously, one comment will be my use of slang in the abstract! Part of the intent of this presentation is to help presenters see themselves through the audience's eyes 2
19 Exact Methods in the NPAR1WAY Procedure Anupama Narayanan,
Donna L. Watts		 Exact nonparametric methods have an advantage over asymptotic methods since they remain valid for very small sample sizes, as well as for data that are sparse, skewed, or heavily tied. However, computing exact p-values by direct enumeration can be very time-consuming, and may be in feasible for many problems. Over the past few years, many new algorithms for exact computations have been pub lished. Beginning with Release 6.11 of the SAS~ System, exact p-values are avatlable in the NPAR1WAY procedure. This procedure uses Mehta and Patel's network algorithm, substantially reducing the computational effort required. The NPAR1WAY procedure computes exact p-values for the simple linear rank statistics based on Wilcoxon scores, median scores, Van der Waerden scores, and Savage scores. Exact p-values are computed for these statistics when the data are classified into two levels (two-sample tests), and when the data are classified into more than two levels (multi-sample tests) sample, null hypothesis, response variable, normal distribution, class variable, clinical trial, probability distribution, exact test, two-sample test 5
20 Formatting and Labeling Variables with SAS Data Set Values Amie Bissonett macro variable, proc step, proc format, label statement, macro function 6
21 Health Care Applications of Statistical Process Control: Examples Using the SAS System Robert N. Rodriguez Health care applications present a new frontier for statis tical process control (SPC) methods. Interest in SPC is driven by a desire to improve patient outcomes in the face of capitation, cost reduction, competition, and changing health care industry standards. This paper illustrates the use of SAS software to analyze health care data with u charts, p charts, control charts for individual measurements, analysis of means for rates and proportions, ilimultaneous confidence intervals for proportions, and basic forecasting macro definition, proc calis 16
22 Hidden Gems in the SAS System Steven J. First The SAS system has a wealth of features that makes it so unique, and sometimes those features are not obvious or easy to find in documentation. This paper will look at several new features, as well as some features that have been around for a while, that we have found to be useful proc step, dataset, proc print, data step, delimited file, macro variable, sas library, trailing @, proc freq 10
23 More Fun With A Saturday Nite Date Deb Cassidy For some reason, almost every presentation I've seen about SAS dates used some catchy title. Maybe it's because working with calendar days isn't the most thrilling SAS code to write but it is often very essential code. This paper will cover a variety of examples for working with SAS dates and times - both basic and advanced. It will include some situations I recently encountered such as the following. How do you know it's a 'Saturday nite date' versus a weekday so having a '0' value for sales is OK? How do you write a production job to keep a rolling 18-months of data? How do you write a production job that will check the date of the incoming monthly file and only run when it is the expected month? How do you merge two files based on date and time when the times are not identical? How do you create a SAS date from a partial date? All code shown here is available in Version 6.10 under Windows. Some may not be availBble in earlier versions or other operating systemS sysdate9, macro variable 10
24 NO MORE MERGE - Alternative Table Lookup Techniques Dana Rafiee This tutorial is designed to show you several techniques available for pulling together multiple sets of data for the macro variable, lookup, data step, merge statement, proc step, array, by group processing, modify statement, proc sql, format statement 6
25 Objects, Objects and More Objects ... Tammy L. Gagliano The dass library in Release 6.11 of SAS/AF software has expanded to include many new visual and non-visual classes. This paper takes a closer look at some of the visual classes and what features they will add to your FRAME applications dataset, catalog entry, where statement, data cleaning 8
26 ODBC: Windows to the Outside World S. David Riba,
Elisabeth A. Riba		 proc sql, proc step, sas log, select, dataset, excel 10
27 Point and Click Your Way to Building Analysis Datasets Betty J. Anderson Working with numerous and individualized databases is a continuous element in our daily research environment. Investigators wish to examine and interrogate their data from many different aspects and end points. There are also frequent times when the final end point can be obtained by programmable calculations using the variables already existing in the database. SAS ASSIST is a task-oriented, menu-driven database system designed to make end users access to the SAS system quick and easy. It's point and click method allows the end user to do complicated calculation with ease, while behind the screens SAS ASSIST is generating the necessary code. It also allows sub~etting of the data to various necessary end points to answer the ever reoccurring questions of the investigators. Using SAS ASSIST provides the novice v.ith a comfortable management environment of the data. This tool allows us to adequately manage some 80 or more unique and separate databases at the same time where statement, dataset 10
28 Randomly Accessing Files Using the KEY=Option Kim L. Kolbe Ritzow The KEY = option on the SET or MODIFY statement is new starting with Version 6.07 of the BASE SAS'" System and allows direct access to an observation nonsequentlally based an indexed value. This paper wHl provide examples as to how the KEY = option is used and compare this type of table lookup technique with more traditional dataset, proc step, modify statement, lookup, set statement, sas log, merge statement, update statement, index, transaction data, proc sql 10
29 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 views with a common LIBNAME reference. Basically, RDB_MAP.SAS outputs a tabular report that shows the names of the SAS datasets ot views as column headings and every variable name that is found in all the datasets or views is in the first column. An 'X' (or your favorite alpha-numeric character or word) is printed in under each dataset or view that it is found in. One can then easily see which tables share a common variable. RDB_MAP.SAS utilizes the SASHELP.VCOLUMN dataset. a PROe SORT, a PROe TRANSPOSE. and a simple PROC PRINT. This is a fast and easy way to display all relationships between multiple tables of information proc step, proc transpose, proc contents, proc print 6
30 Reusable Code: The Lazy Programmer's Best Friend Gary Anderson Clever programmers long ago disCOVered the advantages of borrowing code and modifying it for similar but new software needs. The 'copy and modify' approach saves time in development. However it often leads to libraries of programs that are a nightmare to maintain. The truly lazy programmer looks for ways to write his software only once, or better still, 'borrows and retums software', leaving a minimum of programs to be maintained. This paper will be a tutorial on developing and implementing reusable SAS1) code. It will describe 3 proven approaches to creating effective, reusable SAS code: Pseudo-functions, Included Code, and Exits. Each approach will be explained using a real-life project and actual SAS code. Important environmental issues will be pointed out as well. Strengths and weaknesses of each approach will be discussed macro variable, macro quoting function 9
31 SAS/AF "Gets Focus" Cheryl Olson The ability to detect the exact moment that a widget becomes active or inactive enables SAS/AF Frame entry developers to incorporate functionality into applications that would otherwise be unattainable. In Microsoft Windows, these events are also referred to as "get focus" or "lose focus". A new feature provided to SASIAF developers in release 6.11 enables this capability by way of the _TAB_IN_ and _TAB_OUT _ methods. A widget gets focus or becomes active when the user tabs to the widget or selects the widget with a mouse click. The same widget loses focus or becomes inactive when the user tabs to any other widget or clicks anywhere outside of its region. This paper will suggest how these methods should be used and demonstrate the inability to achieve the same functionality without a TAB IN or TAB OUT sample, data cleaning 4
32 SAS/AF Application Development Using Templates Carl R. Haske Proper applications are logically divided into layers. This 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 usab~ity 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 leaming curve for the end user as they become familiar with many applications developed using 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 7
33 Self-Modifying SAS Programs: A DATA Step Interface S. David Riba There are many situations where it is useful to have a SAse program modify itself during execution. Some examples include: conditiOnally execute a macro based on the data in a SAS dataset conditiOnally execute a procedure when there is no data in a SAS dataset generate in-line SAS program code based on the contents in a SAS dataset write SaL statements for the Sal Pass-Through Facility "on-the-fly" This paper exPlores a little-known routine in the SAS System that allows a SAS program to write SAS code "on-the-fly" during execution. Since CALL EXECUTE is a DATA STEP CALL routine. the full capabilities of the DATA STEP can be applied to conditionally generate SAS program statements while the program is executing. If you have ever written program code to a temporary file and then %INClUDEd it bacJ( into your program, you need to take a closer look at CALL EXECUTE. The paper wiD discuss the uses of CALL EXECUTE With specific examples based on real world situations call execute, dataset, proc step, macro facility, proc sql, proc print, sample, if-then-else, excel, proc sort, macro variable, macro definition 9
34 Taguchi Methods in Experimental Design Ting James Kong quality control, sample 10
35 Testing for and Correcting for Missing Data in Survey Responses: A Survey of Downtown Business in Minneapolis Shelly S. Baxter,
Lawrence C. Marsh		 missing value, regression analysis, proc step, predictor variable, probability distribution, degrees of freedom, null hypothesis, response variable, data science, logistic distribution 10
36 The Beauty of SAS is More Than Skin Deep Charles Wilson,
Arnold Schroeter		 correlation, dataset 5
37 The SAS System in a Data Warehouse Environment T. Randall Betancourt The purpose of this paper is to provide the reader a general overview of the strategies employed in implementing a data warehouse and the role the SAS System plays in these various stepS. While this is not an in-depth methodology, it is an attempt to outline the various steps one would normally go through to implement a data warehouse. In order to make clear all of the terms and acronyms used in this paper, they will be underscored and defined in the glossarY at the end of this paper dimension table, data warehouse, proc sql, fact table, relational database, data standard, foreign key, star schema 12
38 The SAS System: A Complete Client/Server Solution Cheryl A. Garner,
Stephanie Reinard		 12
39 The SQL Query Window Simon Driscoll group by, order by, proc sql, inner join, end= option 10
40 Understanding Control Charting: Techniques and Assumptions Charles Darby Every process has some component of variation, and by measuring that variation directly via control charts it becomes possible to determine when that variation is attributable to randomness (typically termed common-cause variation), or to some identifiable cause (usually referred to as special-cause variation). Two such contrOl charts-the proportion nonconforming or p-chart and the mean value or x-bar chart are important tools for quantitative efforts at quality improvement. This paper will address the components of contrOl charting, the assumptions which form the basis for these chart's construction, the classes of control charts, techniques for quick access to the SAS-QC Control Charting Module via SAS-ASSlS~, and how to recognize changes in chart patterns which might indicate "special cause" variation sample, sample size, bar chart 6
41 Using PROC REPORT in release 6.11 Simon Driscoll dataset, proc report, proc step 10
42 Using SAS Genmod Procedure to fit Diagonal Class Models to Square Contingency Tables Having Ordered Categories H. Bayo Lawal We shall demonstrate in this paper, how the generalized linea.r MODEL procedure GEN MOD in SAS can be utilized to implement the class of models that can be fitteti by Lawal and Upton's (1995) FORTRAN algorithm to square tables having ordered clas sificatory variables. Composite models as discussed by LawaI and Upton will also be fitted to the tables. Applications to 4 x 4 and 5 x 5 square tables will be discussed. Parameter estimates as well as the relevant odds ratios will also be discussed from the SAS output. 149 proc genmod, degrees of freedom, proc step, numeric functions, numeric variable, proc freq 12
43 Using SAS/ACCESS View 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 5
44 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 cycie. Using a SASJAF application as a front-end enby tool can build such efficiencies into program development. Standardized reporting tools developed at STATPROBE. Inc. haYe 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 SASlAF produces a table shell which can later be modified by a SAS programmer to populate the table shell sas programmer, dataset, macro definition 4

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