WUSS 1994 Papers - Index

60 papers. Source: WUSS (Western Users of SAS Software) conference proceedings.

#	Title ×	Authors ×	Abstract ×	Keywords ×	Extras	Pages
1	A Computer Assisted New Drug Application (CANDA) Using SAS/AF Frame and SAS/PH-Clinical	Ai-Yu Wu, Doug Brown	This presentation describes some of the approaches we used in developing a Computer Assisted New Drug Application (CANDA) for use by a Food and Drug Administration medical reviewer. We first describe some strategies for loading clinical data into `SAS/PH`-Ciinical Release 1.0. Second, we describe various `SAS/AF` Frame entries developed to supplement `SAS/PH`-Ciinical.	sas output, temporary dataset, adverse events	source	4
2	A Development Environment for Applications Based on SAS Software	Danielle Davis	Data structures, design methodologies, and programming tools are the foundation components of an application development environment This paper describes these components using a SAS software perspective. Specifically, the paper covers design methodologies, management of appfication components, preparation and maintenance of parallel test and prodlction environments, and reusable code libraries. A sample SAS application 1hat uses the described techniques concludes the paper.	libname statement, catalog, stored macro, sample, proc step	source	4
3	A Matrix Approach to Log-Linear Data Analysis Using SAS/IML	Paul W. Johnson		proc step, odds ratio, cook's distance, proc iml, likelihood function	source	3
4	A Program for Fixing SAS Transport Files on Personal Computers	Glenn H. Itano		dataset, proc step	source	2
5	A Reassessment of the Monetary Approach to Exchange Rate Determination: A Multivariate Analysis of Difference-Stationary Time Series	Victor Gastnaga	Previous attempts to validate the Monetary Approach to exchange rate determination were largely unsucessful. This paper claims that a more appropriate technique, that takes the issue of non stationarity into account, yields positive results. Data for the U.K. and the U.S. are subject to both univariate and multivariate analysis. The Monetary Approach, w~h some qualifications, is validated as a long-run relationship.	interest rate, first difference, time series analysis, unit root, regression analysis, multivariate analysis, sample	source	6
6	A SAS MACRO for the Ricardian Model of International Trade	Zaki Eusufzai	The CONTRAST and the ESTIMATE statements available in the GLM and the MIXED procedures in `SAS/STAT`* system are useful in testing the significance of preplanned linear combinations of treatment means and in estimating mean and SE of linear combinations of model parameters respectively. Constructing the CONTRAST/ESTIMATE coefficients can be tricky and is difficult to understand especially in factorial experiments with the information avaaable in the literature. Thus, an easy to follow method, involving three steps is propossed herein to construct coefficients in CONTRAST/ESTIMATE statements. The three steps include: constructing parameter vectors for all treatment groups, estimating coefficients for the linear combinations, and transferring the coefficients in the CONTRAST/ESTIMATE statements. This method is demonstrated using four examples from single factor, factorial, and mixed model experiments.	proc step, proc mixed, estimate, proc calis, proc genmod, proc glm, treatment effect, sample	source	17
7	A SAS/ETS Application: Forecasting Iran's Agricultural Self-Sufficiency Program	Seid M. Zekavat	This paper intends to make a comparative analysis of the average amount of food required to nourish the growing Iranian population and the amount which is actually available for consumption. The SAS System is used to develop simulation models to forecast the time-frame in which agricultural self-sufficiency may be achieved based on ahemative growth rate scenarios for the Iranian economy. The following models are estimated and used in the simulation: D, - C.,- C, or (8,) * (pop) - (P, + I.J where: D, is the consumption deprivation gap and Cm - C, - Bm (pop.) - P, {1 + il' where: C., and C, represent minimum and actual consumption respectively. Input data for the Iranian economy from 1974 to 1991 is used in the analysis. The SASIETS procedures: `PROC REG`, `PROC PLOT`, `PROC UNIVARIATE` and `PROC ARIMA` are used in the simulation.	proc step, response variable	source	3
8	Access DB2 Tables Using Keylist Extraction	Berwick Chan, Raymond Wan		proc sql, proc step, dataset	source	6
9	Advantages and Pitfalls of the SQL Procedure	Patricia L. Gerend	SQL and traditional SAS software are both capable of defining, manipulating, and printing data. While the use of SQL can result in more concise program statements when merging, renaming, sorting, printing, and obtaining descriptive statistics, traditional SAS software is a much better choice for more powerful statistical computing. Reasons for learning the `SQL` procedure are to simplify data manipulation, to have an independent software tool for the validation of traditional SAS code, and to learn a method of accessing data in relational database management systems. A comparison of SQL to traditional SAS code in performing data manipulation is the focus of this paper. In addition, pitfalls involved in switching from SAS to SQL programming are highlighted.	proc sql, proc step, where statement, missing value, adverse events, sample, proc sort	source	9
10	An Effective Method to Construct Coefficients in CONTRAST and ESTIMATE Statements Used in ANOVA	George C. J. Fernandez	The CONTRAST and the ESTIMATE statements available in the GLM and the MIXED procedures in `SAS/STAT`* system are useful in testing the significance of preplanned linear combinations of treatment means and in estimating mean and SE of linear combinations of model parameters respectively. Constructing the CONTRAST/ESTIMATE coefficients can be tricky and is difficult to understand especially in factorial experiments with the information avaaable in the literature. Thus, an easy to follow method, involving three steps is propossed herein to construct coefficients in CONTRAST/ESTIMATE statements. The three steps include: constructing parameter vectors for all treatment groups, estimating coefficients for the linear combinations, and transferring the coefficients in the CONTRAST/ESTIMATE statements. This method is demonstrated using four examples from single factor, factorial, and mixed model experiments.	proc step, proc mixed, estimate, proc calis, proc genmod, proc glm, treatment effect, sample	source	17
11	Answers To Commonly Asked Statistics Questions	Mike Stockstill	The purpose of this paper is to address some common 'how to' and 'what does this mean' users' questions collected by the statistics group in Technical Support. Product discussion includes `SAS/IML`, `SAS/INSIGHT`, `SAS/STAT`, `SAS/OR`, `SAS/QC`, `SAS/ETS`, and base SAS software. The emphasis is on what can be done with the current releases rather than with future releases, although comments are provided where appropriate. Understanding the presentation requires little or no technical or statistical expertise. The paper should be most useful to site representatives who face a lot of stat-oriented questions.		source	15
12	Calling External Modules from the SAS System	Richard D. Langston	The new MODULE routines allow for invoking external subroutines written in COBOL, C, assembler, and other languages wi1hin DATA steps, SASIIML steps, and SCL steps. This paper introduces the reader to the MODULE routines. These routines are an outgrowth of the COBOUNT routine that has been discussed in previous articles.	character variable, sysrc	source	4
13	Checking Multiple Values for Inequality	Stephen R. Schulz	Consider the case where there are more than two potential sources for the value of a field. For example, there are three :files contributing potential values for a field and each may or may not have missing values. The code to check for missing values and disagreement among non-missing values can get complicated. This paper offers a simple solution to this problem if the fields are numeric and a possible line of attack for character fields. The Problem There are three different :files (actually forms coming from different departments) with fields that may or may not provide a value for a unit of measure code (UOM). If we assume the data are all correct, we can obtain the value simply with the following statement: UOM = max (of UOMa, UOMb, UOMc) ; This easily solves the problem of checking each field to see if it is non-missing and then assigning one of the non-missing values to the output field. Brute Force Solution Unfortunately, the incoming fields may disagree.	standard deviation, missing value	source	2
14	Data Step Trigonometry for the Universal NO Symbol	Kim J. Kubasek	Using pmameters such as radius, stripe width and stripe angle, a `DATA STEP` can be written to generate the X. Y coordinate pairs which descn"be the Universal NO Symbol (as In BOZOS or GHOSTS). These coordinates can be used in an annotate DATA set or to create a font or a map.	do loop, missing value	source	2
15	Developing a SAS System Autocall Macro Library as an Effective Toolkit	Steven A. Wilson	This paper discusses using the SAS System Autocall Facility for the development of a common set of macro utilities for use by application programmers. The autocall facility allows users to invoke a SAS macro without having to define the macro in their current job or session. This facilitates the development of a centralized "toolbox" of SAS macros that many indMduals may utilize. Additionally, the development of an effective autocall library within a systems group allows programmers to quickly perform common processing tasks with consistency and accuracy. Note that this is not a presentation on macro coding. Instead, the focus of this paper is using SAS macros as utilities. Techniques for developing and managing an effective macro library are discussed.	autocall macro, macro definition, macro variable, stored macro	source	8
16	Developing Custom Training Solutions	Chip Rhodes, Claire McCullough	A well-<leveloped training program is essential for users to gain the skills they need to maximize the full power of the SAS System. Recognizing the diversity of users and their training needs, SAS Institute offers a broad curriculum of training span ning several media: self-paced SASITUTOR online training software, video-based courses and tutorials, and instructor based training. There are obvious advantages to a training pro gram utilizing multiple media. Formats can be effectively mixed and matched to allow users to meet their personal training needs. Cost-effective training mixes can also help you stretch your training dollars. Examples of mixed media solutions to training needs are presented for consideration. Efficient use of the SAS System is the common denominator for all organizations seeking training, but each organization has unique elements of operation.		source	5
17	Dynamic Load Balancing of SAS Batch Programs in a VMS Cluster Environment	Rick Levin	One of the perennial problems in SAS system management is clisaibulion of workload among various hosts. Programmers typically are either assigned to only one of the hosts, or must decide on their own which host to use. This paper describes a	sas batch, batch job, dataset, elapsed time, autocall, autocall macro	source	2
18	Elements of Good Programming Style	Amy Caron	The importance of good programming style cannot be underrated. Unfortunately, programmers have a strong tendency to do so. We all like to believe that once a piece of code is put together, however haphazardly, the code will work property from the point it is put into production until forever after. Besides, why waste cleaning up the code it it is only going to be used once? Writing code cleanly the first lime not only increases the chance of getting it right but also eases the task of fixing it in case it is not right Furthermore, chances are likely that the program will be used more than once and it will probably be used by someone other than the author of the code. So in the interest of those writing code and those having to use code that has already been written, some elements of good programming style will be discussed.	proc step, character variable	source	3
19	Empirical Analysis of Food Demand in Peru: Results and the Use of SAS Software	Sumon Kumar Bhaumik	Despite considerable progress in the technology of food, millions of people around the world continue to be and undernourished. It has been proposed that food-feed competition can ag gravate the food crises, and affect the welfare of the poor adversely. This paper analyzes food consumption patterns in Peru using seemingly unrelated regression models, as opposed to the stylized ordinary least square technique. The analysis suggests that food-feed competition is viable in less developed economies that face economic growth, and hence a larger middle class, and increasing urbanization.	regression analysis, predictor variable, proc step	source	6
20	Examination of the Importance of Root Hairs in Plant Water-Use Studies by Repeated Measures Analysis	Carolyn K. Yoder	Root hairs are cylindrical elongations from root epidermal cells that increase the absorbing area of roots greatly. Due to the destructive nature of root sampling, the role of root hairs in relation to plant water-use is seldom investigated. In this study a repeated measures analysis was performed in the SAS System for personal computers to analyze root hair data collected for three species growing in a mixed-grass prairie: Bouteloua curtipendula (sideoats grama), Hilaria belangeri (curlymesquite), and Amphiachyris dracunculoides (annual broomweed).	proc glm, proc genmod, repeated measures, repeated measures anova, proc step, sample, correlation, anova	source	4
21	Experimental Design and Survey Sampling Methods Using the SAS Macro Utility	Paul W. Johnson	This work involves using SAS macros for the selection, estimation and transformation of sample survey data. The macros are for use in "Experimental Design and Survey Sampling Methods". The macros are set up for use in: a) Selecting the sample size for estimating population parameters of interest (the mean μ, the total τ and the proportion P) in stratified random sampling. b) Estimating population parameters of interest (the mean μ, the total τ and the proportion P) in stratified random sampling. c) Estimating population parameters of interest (the mean μ, the total τ and the proportion P) in cluster sampling. d) Estimating population parameters of interest (the population ratio R, the ratio mean μᵧ, and the ratio total τᵧ) using ratio estimation. e) Estimating the population proportion in such a way as not to identify individual responses. This is the random response model. f) Calculating the number of callbacks that should be made to make optimal precise population parameters [a solution to the issue of nonresponse]. g) Finding the power transformation needed to transform the data to follow more closely the normal distribution. h) Calculating the cut-off points of the strata such that an optimal allocation of the sample between strata is made.[Cumulative Square Root of the Frequency Method] The library contains SAS macro routines for the selection, estimation and transformation of sample survey data. The set of macros can be found in eight subdirectories namely: (A,B,C,D,E,F,G and H). The series of Statistical Analysis System macros have been placed in the Internet Computational Biology Gopher at Johns Hopkins University and are available from the Biodiversity and Biological Collections Gopher as of March 1994.	sample, sample size, likelihood function, macro definition, parameter, macro put, cluster sampling, proc freq, dataset	source	7
22	Factors Determining the Fluctuation of the Dow Jones Industrial Index Using SAS Procedures	JiHong McDermott, Anne-Marie Mowad	Many variables may influence the movement of the Dow Jones Industrial Index. I hypothesize that the Federal Funds Rate, the percentage change in the M2 money supply, and time are three of the most influential detenninants. Therefore, through use of the SAS System and SAS procedures, I tested my hyporthesis to detennine its reliablity and validity.	predictor variable, correlation, response variable, regression analysis	source	3
23	Forecasting College Enrollment Using SAS/ETS Procedures	J. Richard Earley	This paper investigates use of the SAS System in analyzing college enrollment activity to forecast enrollment statistics in relation to acceptances and applications. Consideration was also given to tuition, student-teacher ratios, and to public versus private institutions. Data was compiled for eighty-five California colleges and one hundred eleven colleges in New York, using Lovejoy's College Guide, copyright 1992. The SAS System was then used as the primary tool for developing and estimating statistical models.	proc step, p-value, regression analysis	source	4
24	Formats: A Beginner's Tutorial	Richard D. Langston	This tutorial will introduce the beginning user of the SASs System to the concept of formats. Several Institute-supplied formats will be described so that the user can better understand the concept. Then, `PROC FORMAT` will be Introduced as the method by which the user can produce custom formats. Various features of `PROC FORMAT` are discussed. including ranges, exclusion ranges, LOW/HIGH/OTHER, informats, PICTURE, and the CNTLIN= data set.	proc format, proc step, date variable, decimal, sysdate9	source	4
25	Formats: An Advanced Tutorial	Richard D. Langston	This tutorial discusses several advanced features of format processing that can be of interest even to knowledgable users of the SAS System.lterns covered Include: using formats as labels, cndout and cntlin data sets, gaining efficiency with the the NOTSORTEO option, using a format as an alternative to sorting large data sets, and comparing VS and V6 formats.	proc format, proc step	source	4
26	From Multi-Minute to Sub-Second Response Time With Indexes	Terry Berryhill	At Pacific Gas & Electric Co., many datasets include more than 1 million observations, and our largest disk databases are thousands of tracks-they may exceed 1 gigabyte. We are very interested in ways to reduce processing time. Many of our applications involve selecting a few records to display from a large dataset. The old way to do this was to create a temporary dataset which was a subset of the large dataset. The new way to do it is to use indexes. Once we pay the up-front cost to create an index, we can select a few records in a fraction of a second, compared to more than a minute the old way. These dramatic performance gains show up in elapsed time, in CPU time, and in I/O (input/output operations). In the applications where I get improved performance with indexes, I am only selecting a few observations or even a single observation. This is the key to useful indexing in SAS.	cpu time, index, where statement, proc step	source	2
27	Generating Graphics Using DSGI (DATA Step Graphic Interface) Enables Mouse Selection of Graphic Points	Bruce Kayton			source	3
28	How to Print SAS/Graph Output from MVS on Printers Connected to a LAN Using TCP/IP	Marvyn M. Lindsey	The objective of this paper is to demonstrate how sites that have `SAS/GRAPH` only on a mainframe platform without a high resolution graphics printer can print `SAS/GRAPH` output by using TCPIIP to route the output to postscript printers connected to aLAN. The paper will demonstrate how the CSU Chancellor's Office prints `SAS/GRAPH` output to various postscript printers on an Apple Talk network from an IBM 4381 MVS/ESA system via a VAX 6230 and via the LPR capability of TCP/IP. Coding of the appropriate `SAS/GRAPH` options to create postscript output, the use of the LPR command, and the setting up of the print capture files on the IBM and VAX systems will be discussed.	sas log, options statement	source	4
29	If I'm Not a Database User, What Is the SQL Procedure Good For?	Ann Olmsted	SAS* `PROCEDURE SQL` may offer the simplest way to perform several common and not-so-common tasks, such as taking Cartesian products of SAS data sets (combining every observation in one data set with every observation in another), creating macro variables, adding summary statistics to a SAS data set, producing simple reports, and performing set operations (union, intersection, difference). Complete examples are given, plus a quick reference card, plus a list of `PROC SQL` traps for novices (so you won't make the same mistakes I did).	proc sql, proc step, dataset, order by, create table, macro variable, proc means, group by, full join, macro definition	source	15
30	Implementing Client/Server Applications in a Heterogeneous Platform Environment	John McIntyre, Daniel J. Squillace	While client/server computing suggests to the casual observer a configuration of a personal computer connected to a "server" machine. to the system implementer it can be much more. Few enterprises find themselves in the position of designing their hardware architectures from "scratch". Rather, they more often are faced with implementing a distributed environment across a landscape of varied hardware and communication platforms. Selecting the proper platform for the execution of the logical segments of an application means knowing about the relative strengths and weaknesses of those platforms. This paper will review the requirements of the logical segments of applications, and compare those to the strengths of a variety of client and host based systems.	data warehouse, proc sql	source	9
31	Importing SAS Graphic Files into WordPerfect Version 5.2 (Comparing Several Device Drivers to Determine which Produces the Best Results)	Lori D. Griffin	This paper demonstrates several different device drivers that were used to import a SAS graph into WordPerfect The ultimate goal was to determine which device driver displayed the best result. Criteria for best result was that the imported WordPerfect graph closely resemble the original graph. A comparison process took place between examples of each imported WordPerfect graph and the original graph. Several aspects were taken into consideration in this process, such as color to color. transfer, font styles, and the size of the files that were compared. Two different graphs, an annotated pie chart and a box and whisker plot, were taken through this comparison process. The comparison process began with the device drivers recommended by WordPerfect. Next were the device drivers recommended by SAS. Concluding the process was a modified SAS device driver. The last device driver proved to have the best result.	bar chart, pharmaceutical industry	source	8
32	Introduction to SCL Lists	Roger Staum	The SCL list is a flexible and powerful data structure which first appeared in version 6.07 of the SAS system. This paper will help you: understand what SCL lists are, and how they differ from other data structures decide whether a particular application is a good candidate for an SCL list learn SCL list terminology classify SCL lists and items by access, type, and attributes manipulate SCL lists using special functions and routines plan for future enhancements to SCL list technology		source	10
33	Joining Tables of Data in the SQL Procedure	Kirk Paul Lafler	Joining two or more tables of data is a powerful feature found in the relational model and the `SQL` procedure. Often, the need to analyze or process data that resides in two or more tables is necessary. When this is the case, a common or cotmecting column is used from each table to form the basis for the join. Consequently, it is possible to discover new and exciting relationships between data. This paper illustrates what a join is, why joins are necessary in data analysis, the concept of joins and the Cartesian product in relational theory, and the nmnerous types of joins that can be performed. In particular, participants will learn how to perform basic join operations on two or more tables (inner joins), specey join conditions, and perform left, right, and full joins (outer joins) using SAS System data sets (tables).	proc sql, data merging, proc step, right join, full join, left join, inner join, proc sort	source	6
34	New Developments in SAS Three Dimensional Visualization	Ali Dogrusoz, Stuart A. Nisbet	In this paper. we present some of the current thre~imensional visualization development efforts of the computer graphics division at SAS Institute. We will discuss the current functionality in SASISPECTRAVIEWn.o and SASINVISION"' software. We also discuss a new product, Visual Space...., as well as ideas for their future directions and applications. Although it is in the R&D stage, we have included it in this paper to provide a feel for some of the avenues we are exploring in this ever-growing area of three dimensional computer graphics.	data visualization, scatter plot	source	5
35	Programs That Write Programs: Creating Code Generators in SAS	Michael C. Harris	SAS code generators are a special class of programs that automate the creation of source code for `PROC` steps, DATA steps and host-specific procedural languages, such as the DOS batch language or Unix scripts. They may depend on predefined data dictionaries for input, or may extract information from non-SAS files whose general structures are documented, but whose actual content may be application-dependent. Database files are one example of such files. This paper discusses issues involved in planning, implementing, testing and debugging code generators written in the SAS `DATA STEP` language. Examples of different approaches are presented, and points to consider when packaging a code generator in SAS macro language are touched upon. Why Write a Code Generator? In general, computer programs are written for a few good reasons. We may want to automate an error-prone process that was previously performed manually.	proc step, proc print, data dictionary, data step, input statement, proc contents, dataset, macro definition, macro loop, %if-%then-%else, macro variable	source	6
36	ROBOSAS: Laboratory Automation and SAS	Charles R. Villarrubia, Seth Michelson, Ronald Rhodes, Edward Leung	This paper describes the process of laboratory automation and the role SAS software can play in application development. Laboratory automation is a process of converting routine, repetitive tasks, performed by humans in a laboratory environment, to machine executable tasks supervised by human monitoring. This involves seamless integration of data collection, analysis, reporting, and database storage subcomponents across disparate platforms. Pure applications, which depend on one software package to accomplish these goals, are easier to maintain and development. Mixed systems exploit a variety of software to perform these same purposes and provide flexibility to system development. Concepts and tools from systems analysis and forethought in designing applications are crucial to a project's success. An example of a laboratory automation project highlights these points.	raw data, data science	source	7
37	SAS in Taming Classical Violations	Kamal Shoukry		estimate, predictor variable, correlation, autocorrelation, proc step, proc calis, residual, proc autoreg	source	3
38	SAS/DB2 - Do's and Don'ts	Michael L. Sperling		proc sql, proc step, where statement, select	source	5
39	Speedy Data Retrieval and Display in a SAS/AF System: A Case Study	Louise Weiler, Standish Sibley, Tim Berryhill	Developers of `SAS/AF` systems must strive to minimize h~w long users wait for each screen display. Short screen watts are particularly challenging when displaying data that must first be retrieved from a very large data base. This paper will show how, using features new to Version 6.07, a real.life `SAS/AF` system went from impulse power to warp dnve. This system was developed on MVS but the concepts and capabilities are applicable to all platforms.	set statement, key=, character variable	source	4
40	Techniques for Efficiently Accessing and Managing Data	Steven A. Wilson	This paper explores a number of SAS System data management and coding techniques for improving efficiency. After efficiency is defined and a number basic efficiency techniques are summarized, some SAS Version 6.07 + features are discussed from an efficiency viewpoint. These features include `PROC SQL`, SAS data set compressing, the Stored Program Facility, and SAS Data Views.	proc step, dataset, proc sql, elapsed time, proc sort, view, character variable, proc print, where statement, macro definition, sas programmer, macro facility, %if-%then-%else	source	10
41	Techniques to Avoid: What Momma Should Have Told You About SAS/GRAPH	Arthur L. Carpenter	Several available graphic options and PROCedures produce graphs and charts that are either misleading or do not convey the information intended by the creator of the graphic. This paper demonstrates a few of these commonly applied `SAS/GRAPH` graphics and options, and discusses their pitfalls and why they should be avoided. The ability to distinguish values and to interpret graphics depends on our perceptions, and we do not always perceive what we think we do. Research has shown that some types of graphs and some combinations of graphical elements are more easily and accurately interpreted than others. Correct selection of the elements can lead to a strong presentation, while other combinations of these elements can be misleading or even deceptive.	proc step, proc gplot, histogram	source	4
42	The 'SKIP' Statement	Paul H. Grant Jr.		macro definition, proc step	source	2
43	The Asymmetric Weighting of Service Encounters	Kersi D. Antia	The differential weightage given to negative infonnation in impression fonnation has been well documented in the psychological literature. Little has been done, however, in examining the effects of extremity and valence of service encounters on consumer evaluations of the service provider as a whole. This paper attempts to explain the change in evaluation of a service provider as a function of the encounter. Encounter extremity, valence and their interaction are found to be highly significant predictors of change, but in the long term, the service firm's reputation is found to mediate any change in evaluation. (Key Words: Service evaluation, extremity, valence, reputation,).	service provider, sample	source	6
44	The Benefits of Object-Oriented Application Development Using the SAS System	Randy Pierce	The SAS System can now take full advantage of the object-oriented (00) paradigm. There are volumes of materials describing the benefits of object-oriented programming in general. There are also manuals describing how to write 00 appncalions with SAS software. This paper describes why you may want to use 00 techniques when writing applications based on SAS · software. Object-oriented programming (OOP) is a refinement of modular programming. SAS Institute has provided 00 constructs that build upon existing modular programming techniques available to Screen Control Language (SCL) programmers. As a result, well-Written modular SCL programs are but a step away from becoming classes in a class hierarchy. A class hierarchy can act as a set of generic tools that can be applied to virtually any application.	catalog entry, sas base	source	9
45	The Future for SAS Software	Tim Lehman	This paper discusses what's on the horizon for SAS Institute products-the development directions planned, new SAS System components on the way, and new supported hardware platforms. As a framework for discussion, it's helpful to review the barriers that the SAS System overcomes for your organization: diverse data sources, applications that need to be integrated, users with differing degrees of computer experience, and your own unique hardware requirements.	structured data, excel	source	3
46	The Joys of Merging: Alternative Techniques	Joan Keesey	The SAS System"' provides the capability of performing one-to-one and many-to-one data set merges easily and efficiently via the `MERGE` statement. Many-to-many merges require alternative techniques but are often very useful, particularly when there are errors and inconsistencies in the merge variables or when there is a "best'' match based on some criteria, i.e., the record with the highest score or the record which best satisfies some formula or requirement. Using a many-to-many merge technique provides the user with increased flexibility in searching any number of potential matches for the "best' match. The implementation of a many-to-many merge can eliminate repeated merge steps and make more efficient use of the matching information.	proc step, proc transpose, point= option, proc format, set statement, macro variable	source	6
47	The Lazy Man's Guide to S-A-S	Ginger Carey, Helen D. Carey		sample, proc step	source	7
48	The Use of SAS Regression in Analyzing a Major Sporting Event: The Case of the 1994 Masters Tournament	William Orzeck, Joseph E. Earley	Using a cross-section data set derived for the 1994 Masters professional golf tournament, the authors developed an econometric model formalizing the reasons for the various levels of performance. The Masters participant's score is used as the dependent variable. Regressors were selected which are believed to be integral to the performance of excellent golf.	proc step, proc reg, correlation	source	5
49	Tips From a First Time FRAME Application Developer	Robin Reese	The following paper describes tips and techniques that proved helpful in developing a FRAME application under Windows.		source	4
50	Up to 50 x SAS Performance Gains on Large Data Volumes Using Scalable Parallel Computing	Jesse Davis, Helen Spade	Turning large volumes of historical data into valuable information to support the decision making process of management is a growing need of corporations in the 90's. However, the ability to perform fast data reduction on large data volumes is limited by traditional computer systems which can take hours of CPU time and days of elapsed time to process multi-gigabyte datasets. This paper describes how one of my customers in the health care industry addressed the volume issue in health decision support processing and improved the end user's toolsets. The paper describes the problems encountered while trying to achieve their business goals, and the hardware and software solution implemented to resolve these problems. Actual performance numbers are given for Tabulate, Select, 3-way Join, Nested Select Queries and a multiple user test.	data science, elapsed time	source	6
51	Using PROC SQL Dictionary Tables to Generate Lists for SAS/AF Extended Tables	David Freese	`SAS/AF` software provides the capability of easily retrieving information about SAS libraries, directories, catalogs and datasets. Starting with SAS 6.07. `PROC SQL` provided support for a series of new functions. Using SAS data sets generated from various `PROC SQL` dictionary tables you can quickly fill and customize extended tables which display data-driven selections. This increases programming flexibility, uses current information to drive user selections, and reduces the time and effort to adjust or enhance `SAS/AF` and Screen Control Language (SCL) source code. For instance, if you store a set of `PROC REPORT` templates in a catalog and you want the user to be able to choose from among the various reports, you can retrieve all the information about this catalog (i.e. `LIBNAME`, catalog, report name, extension, label, date created, etc.) by using the `SQL` procedure dictionary table.	proc sql, proc step, dictionary tables, catalog	source	3
52	Using SAS to Determine the Factors that Label College Students as "Computer Hackers" at two Los Angeles Universities	Annaliza Dialino	The purpose of this paper is to discover, with the use of SAS', the factors that best determine if a college student is a '"computer hacker"; a person who spends the majority of their leisure time using a computer. and takes pride in being able to successfully "hack" into a computer software. The methodology used was a personal characteristic survey distributed at two Los Angeles based universities, Loyola Marymount University and the University of California, Los Angeles. An econometric model was then developed specifying the number of hours spent on the computer as the dependent variable. A sample of the independent variables used (i.e., regressors), includes grade point average (GP A), gender, and a question requesting the number of hours spent on the computer per week. These hours were then allocated to correspond to specific programs such as the Internet, WordPerfect, or a progranuning language.	response variable, predictor variable, proc step	source	3
53	Using SAS/AF, SAS/FSP, and SCL to Create a User-Friendly Data Entry System	Elizabeth Li	`SAS/AF`, `SAS/FSP`, and Screen Control Language (SCL) allow you to create a user-friendly data entry system. This paper presents an example of a system that uses `SAS/AF` and SASIFSP to interface with users. The system contains screens for data entry, data retrieval, and report generation. Data safety and validation techniques also are addressed. The paper presents techniques to build a data entry system with `SAS/AF` and SASIFSP. The approach can be applied to data entry in any field. Although, the system is built on PC-SAS, these techniques can be used on any platform.	proc step, data cleaning	source	5
54	Using the SAS System to Measure Factors Determining Success by Those Majoring in Theatre at the University Level	James D. Ryan	The purpose of this paper ia to present a methodology in which the SAS System may be used to investigate the Attribute Characteristics Profile of a population of university/collage theatre am students. The paper presents the results of a state wide questionnaire invutigation of the physical. personal. family and academic characteristics of theatre students in Kansas. The SAS S y.tam was used u the primary tool of investigation. In addition to using the tracfotional crosatabulations and descriptive atatlatica provided by `PROC FREQ` and `PROC UNIVARIATE`. the otudy empiP.)'II the statiaticaUy powerful techniques of `PROC CORR`. `PROC REG`. `PROC` STEPWISE and `PROC` RSQUARE. An econometric model ia developed using student grade point average _in theatre courses ** the number of theatre cou,.es taken. male/female, and numerous other variables.	proc step, proc reg	source	3
55	Visualization of Scientific Data: Specialty Graphs Without Using Annotate	Arthur L. Carpenter	`SAS/GRAPHTM` is flexible enough to create many graphs and charts that would not normally be considered standard `SAS/GRAPH` output. Although the ANNOTATE Facility is often used to "dress up" a graph, there are a number of non ANNOTATE techniques which can also be used to create non-standard graphics. The examples illustrated in this presentation use the technique of data manipulation to "trick" BAS/GRAPH into producing graphs and charts that at first glance appear to be outside of its capabilities. This technique uses the incoming data to create additional data points. These data points are then manipulated and used in conjunction with the SYMBOL and PATTERN statement. When created in the proper sequence these additional data points can create error bars on scatter plots, histograms, butterfly plots, box-whisker plots, histograms with broken scales, multiple axes, and special shapes and symbols.	proc step, histogram, proc gplot, box plot, proc calis, scatter plot, missing value, outlier, proc sort	source	9
56	Working with SAS Date and Time Functions	Andrew H. Karp		sysdate9, datetime variable, date variable, datepart, numeric variable, proc freq, raw data, time series analysis, time variable, proc step, if-then-else	source	5
57	Wow, It's Sooo Simple (My First Encounter with Proc Report)	Angie C. Wang	As a Consultant for Coopers & Lybrand, I use SAS to develop many applications at client sites. At CitiBank, I was asked to develop a reporting system that measures the cost-effectiveness and response rate of direct marketing campaigns. As a result of this project, I learned to use both `PROC SQL` and `PROC REPORT` for the first time. I was impressed by how easy it was to learn as well as how good the layout looked without a big time investment. This paper will briefly describe the development process and then will focus on how `PROC SQL` was used to manipulate the data and how `PROC REPORT` was used to create the report and its ease of use.	proc step, proc report, proc sql	source	6
58	Writing SAS Programs that Work	Susan J. Slaughter, Lora D. Delwiche	There are some things you can do to make it more Hkely that your programs will work and make it easier to figure out what's wrong when they don't work. Make your programs easy to read, test each part of your program before going on to the next, and test your program with simplified or smaller data sets when appropriate. If your program doesn't work, there are a few steps you can follow that will make it easier to find the source of the problem. Read the SAS log. The SAS log has many messages in the form of notes, warnings, and errors all of which are important in determining the source of the problem. Always start at the beginning of the log and look for simple mistakes first.	sas log, error message, proc step, dataset, input statement, raw data, missing value, proc print, sas programmer	source	6
59	Your Program Works, But is it Efficient?	Sheree H. Anderson	Usually errors are thought to be logical and syntactical in nature because they prevent a program from successful completion. However, a well-trained user community also recognizes inefficient processing as a type of error even though inefficient programs can execute successfully and lead to accurate results. For most applications, it is possible to develop more than one	proc step, output	source	3
60	ZAP to ZAPS	Jason Moore		dataset, proc step, proc copy	source	7

Back to Conf go 1995 go 1993

This site serves as a convenient hosting location and does not work as a publisher. All copyrights belong to their respective owners.

The information on this site is provided for general reference purposes only. Whilst every effort is made to ensure that the site is up to date and accurate, no warrant, nor any responsibility or liability for, the accuracy or completeness of the content or for any loss which may arise from reliance on information contained in this site is provided. Links to other sites are provided for your convenience but no responsibility or liability for the content of those sites or of any external site which links to this site is accepted. References to any specific commercial product, process, service, or corporation are also for information only, and do not constitute endorsement, recommendation or favoring.

SAS is a registered trademark of SAS Institute Inc. SAS, Statistical Analysis System, and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration.