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BUGSMWSUG 1992 Papers - Index
46 papers. Source: MWSUG (Midwest SAS Users Group) conference proceedings.
| # | Title× | Authors× | Abstract× | Keywords× | Extras | Pages |
|---|---|---|---|---|---|---|
| 1 | A Corporate Revenue Planning Application Using SAS/AF | Joseph S. Bartling, William F. Vander Lippe |
dataset, macro variable, batch job | 6 | ||
| 2 | A Monte Carlo Evaluation of the Rank Transformation for Cross-Over Trials | George W. Pasdirtz | sample, monte carlo, proc step, regression analysis, normal distribution, correlation, sample size, treatment effect, standard deviation, bootstrap, response variable, numeric functions, parameter, anova, main effect | 6 | ||
| 3 | Accessing the SAS Usage Notes and Zaps Over Bitnet | Barry W. Grau | sample, sas/ets | 5 | ||
| 4 | An Advance in Geographic Information Systems using SAS Software: Address Lat-Longing | Doug Surch | proc gmap, sas output | 6 | ||
| 5 | An Efficient Way to Produce Multiple Graphical Representations | Alice M. Cheng | dataset, macro variable, options statement, data step, macro definition | 10 | ||
| 6 | Books By Users For Users | David Baggett | In this paper, SAS Institute's acquisitions editor gives an overview of the institute's Books by Users program and explains how, as a SA$' software user, you can benefit from It. Through the Books by Users program, SAS Institute publishes and makes available to its users bOOks about the SAS System written by SAS users. The Books by Users program was develOped as a means of building a library of h~uality bOOks about the SAS System to complement primary referenoe and usage documentation developed by the Insti tute. The bOOks offered through the Books by Users program docu ment useful applications and represent some of the best ideas in the SAS user community | sas programming, regression analysis | 4 | |
| 7 | Creating Interactive User Windows Without Using SAS/AF | Kathy Shelley | if-then-else, proc freq, proc step | 5 | ||
| 8 | DATA Step Changes and Enhancements | Jeffrey A. Polzin | dataset, modify statement, do loop, by group processing, output, select, set statement, leave, sample, proc sort, proc step, master data management, update statement, automatic variable, composite key, continue | 6 | ||
| 9 | DATA Step Performance | Pat M. Herbert, Jeffrey A. Polzin |
For production sites, several changes in Release 6.07 will help reduce DATA STEP CPU usage. One of the first concerns In produc ing Release 6.07 was SAS data set 110 because the vast majority of DATA steps produce SAS' data sets and a large number of them also read SAS data sets. Another major concem was IN FILE perfor mance. From tests on Release 6.06. ~ was ciear that Reiease 6.06 unformatted extemal fne input was faster than Release 5.18 exter nai input. This lead to benchmarking of aU informats, which were one source of poor perfonnance. Another source of poor INFILE performance was column pos~ioning. In Reiease 6.07, DATA STEP column positioning has been improved, especially positioning expressions such as offset+5 * +5, and @5. Similarly. informats have been improved by up to 700%. Special attention has also been paid to DATA STEP functions. Perfonnance has aiso improved when output variables are being created and when the number of vari ables defined in the DATA STEP Is large |
dataset, cpu time, missing value, options statement | 5 | |
| 10 | DATA Step Views | Jeffrey A. Polzin | Traditionally. SAS'software programmers used the DATA STEP to extract data from external flies In order to store the data in SAS data sets for subsequent use by SAS procedures, The DATA STEP view provides an alternative method of accessing and managing data transparently. DATA STEP views inherit the power and flexibilty of the DATA STEP. with the ability to manipulate and manage data from a variety of sources including external files and existing SAS data files. This paper describes the input and output DATA STEP view conceptual models. the application uses of each type. the definition process for each view type. restrictions and requirements. and extensions to the DATA STEP language to support DATA STEP views. Performance issues of CPU. 110, elapsed time, and memory utiliza tion are discussed with comparisons to earlier data extractiOn meth ODS. More detailed examples and discussion are provided to demonstrate the more complex uses of DATA STEP views |
proc step, dataset, sample, proc sort, modify statement, proc print | 6 | |
| 11 | Developing Applications for Enterprise Information Delivery with SAS/EIS Software | Margaret A. Crevar | dataset, vertical bar chart | 3 | ||
| 12 | Developing County Profiles using PROC SQL | Arlene Slocum | proc sql, create table, data step, order by, proc step, macro variable, sample, alter table, macro definition | 6 | ||
| 13 | Developing SAS Applications Using Information Engineering Methodology | Priscilla Van Grevenhof, Roger Mueller |
The Mayo Clinic adopted IE (Information Engineering) methodology as the standard development methodology for systems in 1988. The Texas Instruments IEF (Information Engineering Facility)'" Toolset was the automated toolset chosen for application development. For institutional data the target platform is DB2.... In the Department of Health Science Research IE methodology is also used but the target platform may not be DB2. The many research projects done at Mayo are short lived, from 1 to 3 years, and one of the tools used is SAS.~ SAS as the target platform is chosen because of its flexibility and short development time. These attributes match the needs of the research community. This poster will show how IE methodology is used to develop a SAS application and how IEF objects are related to SAS objects | dataset, libname statement | 4 | |
| 14 | Effective and Efficient Use of SAS/GRAPH Software | LeRoy Bessler | bar chart, horizontal bar chart | 10 | ||
| 15 | Electronic Mail | Judi D. Reine | 3 | |||
| 16 | Enhanced Support Services from SAS Institute's Technical Support Division | Sally J. Painter | At SUGI 17, the Technical Support Division announced three new support services availableto SAS software installations. These three new features, in addition to the existing Online Customer Support Facility, offer a full range of electronic support services. The electronic support services available are: Electronic Mail Interface to Technical Support (EMITS) Online Customer Support Facility (OCSF) TSNEWS-L File and Mail Ust Anonymous FIP These services allow SAS Software Representatives, Consultants, and users to communicate with the Technical Support Division electronically. lbi.s paper will discuss the services with an emphasis on the best way to utilize each. There will also be a diSCUSsion on other enhancements to Technical Support services | proc print, sas log | 7 | |
| 17 | Introduction to Release 6.08 SAS/INSIGHT and SAS/LAB Software | Mark Brown, Marshall P. Scott |
Recent trends in data analysis techniques are now avalable to SAS software users with SAS/LAB and SAS/INSIGHT software, two key components of a data analysis strategy that are part of the SAS System for Information Delivery. SAS/LAB software is a data anaIy· sis advisor for users without an extensive statistical background. As an analysis proceeds, SAS/LAB software offers explanations of the results and suggestions for further analysis. SAS/INSIGHT soft· ware is a graphical data analysis tool that offers interactive statistical graphics combiled with traditional statistical techniques. This paper provides an introduction to SAS/LAB and SAS/INSIGHT software |
box plot, scatter plot, regression analysis, data science, response variable, histogram, proc reg, by group processing | 6 | |
| 18 | Macros for Converting PROC FREQ and PROC UNIVARIATE Output Files into ARRAY Form for Data Analysis on a Large Scale NDA Clinical Trial Database | Hugh Geary | proc step, macro loop, sas output, macro definition, proc freq, do loop, macro call | 6 | ||
| 19 | Management of Time-Range Data | Andrew A. Norton | proc sql, proc step, create table, missing value | 6 | ||
| 20 | Marketing Research: Uncovering Competitive Advantages | Warren F. Kuhfeld | The SAS@ System provides a variety of methods for analyzing marketing data including conjoint analysis, correspondence analysis, preference mapping, multidi mensional preference analysis, and multidimensional scaling. These methods . allow you to analyze pur chasing decision trade-offs, display product position ing, and examine differences in customer preferences. They can help you gain insight into your products, your customers, and your competition. This paper discusses these methods and their implementation in the SAS System | conjoint analysis, proc princomp, proc corresp, proc step, nominal variable, data science, data visualization, predictor variable | 9 | |
| 21 | Micro <-> Mainframe - Forte PJ | David M. Wheat | 11 | |||
| 22 | Modifying a Postscript Printer Definition to Produce a Negative Image for Typesetting | Larry Hoyle | proc step, modify statement | 6 | ||
| 23 | PC/SAS Installation Made Easy | Randy Van Beek, Stan Nielsen |
5 | |||
| 24 | PROC REPORT: An Introduction to the Batch Language | Ray Pass | proc report, proc step, proc print, sample, character variable, format statement, class variable | 10 | ||
| 25 | SAS Efficiency Techniques | David Sommer | decimal, numeric variable | 4 | ||
| 26 | SAS-L: An Electronic SAS Discussion Group | Nancy Hill | macro definition, statistical software | 6 | ||
| 27 | SAS/AF Graphics Device Applications | David M. Wheat | if-then-else, dataset | 16 | ||
| 28 | Simplified Selecting: A Comparison of SCL Selection List Techniques | Frank C. DiIorio | catalog entry, dataset | 7 | ||
| 29 | Supporting SAS in an Academic Environment | Nancy Hill | sas consultant, sas library | 5 | ||
| 30 | The Advantages of SAS 6.06 Under OS/2 | Stephen Mandel | This paper prssents !he author's experience in working with OS/2 $AS in an environment that includes $AS for !he PC, IBM and VAX environments. The discussion includes how well OS/2 $AS Interfacss with !he OS/2 PCSAand 3Com network protocols as weN as other OS/2 applications software. A Beta copy 01 SAS 6.06 was installed on a GRioJS6is running IBM OS/2 1.2. The processor is a 25 Megahertz 386 chip with B megabyles of RAM memory installed. There is no math coprocessor. AD SAS Instit~e soltwane P'QIlUCIs were ilstalled on this mac:hine includill9. Base , SASJSTA~ SAS/FS~ SASIGRAP~ SASIETS~ SAS/ASSIS~ SASnML ~ SASJOrfi!! SAS/ACCESS', SASICONNECT', SAS/A~and SAS/Q~ Compressed SASIGRAPH maps were also installed. Together, the software required about 65 megabytes of hard disk space. A benchmark program was created to measure performance of 1I1e OS/2 version 01 SAS |
proc step, missing value | 4 | |
| 31 | The Development of a Cost Recovery / Chargeback System for Printing | Vickie L. Custer | macro variable, call symput | 8 | ||
| 32 | The DynaLink System | David Sommer, David Goossen, Andrew M. Traldi |
data dictionary, sample, proc step | 6 | ||
| 33 | The Evolving Role of the SAS System in the Development of the Production System for the Consumer Price Index (CPI) | James E. Johnstone, Stuart Leven |
The Bmeau of Labor Stali&tics (BLS) produces a number of economic indic:a!ors measuruig changes in various market sectors, among them the Consumer Price Index (CPl). This index ~ using a probability sample, the change in price of a fixed mukct basbt of consumer goods and services in specific geograpbk: areas as well as by region and across the U.s. The impact of !he index is far reaching. In the 1986 SUOI Proceedings, the role of the SAS System in the development of the zevision of the associated production system was discussed. This revision came on-line in 1987. This paper discusses expeIi_ in five years of productiOll use of the SAS system in this envinxunent, the fau1ts and foibles uncovered, and the role of the SAS system in maintenance in a real-life setting of this iaJge-Icale system | sample, proc step, imputation, macro facility, macro variable, dataset, macro definition, proc sql | 10 | |
| 34 | The SAS System Enters the Third Dimension Using DATA Step Views for Real-time Quality Control | Jeffrey A. Polzin, Robert N. Rodriguez, James F. Sattler |
The SAS·System is developing rapidly and in many ways as it approaches the 215t cenlU'y. This paper deals with one set of quan titative changes and shows how these changes, in combination, usher in a new qualitative change. As a result of new developments at the supervisor, procedure, and host levels, the SAS System is moving beyond batch and interactive processing capabilities and into anew, third dimension of real-time and event-driven processing. This opens up entirely new vistas for applications developers | sample, proc step, dataset, sysrc | 5 | |
| 35 | Totally R.A.D. With SAS Screen Control Language | Robert W. Simmons | This paper discusses Rapid Application Development with BAS' Screen Control Language within mM's Virtual MacbinelEnterprise Systems Architecture (VMIESA). Specifically, it includes enmples and source code for legends, menus, pop-up windows, single-row data entIy screens, and multi-row data entIy screens | data cleaning, sample, if-then-else, proc sql | 9 | |
| 36 | Use of DrawPerfect Software to Modify and Annotate Graphs Produced by SAS/GRAPH | Paul D. Evenson, Randall D. Van Beek |
The purpose of this paper is to demonstrate how easy it is to change and annotate SAS/GRAPH" plots. First, we will demonstrate how the plot would look if we created it in SAS/GRAPH and sent it directly to a Hewlett Packard LaserJet III". Note in the 'goptions' that the device was set to BPLJS2, the acronym for the laser jet printer, and the name of the file that contains the plot was GAllGASAS.PL!I!. Note also that the log indicates that it took 1.33 minutes to create the plot which is printed in the rotation=portrait, form. is in Fig. 1. default, This plot We used PROe G3D with the SCATTER option to create this graph. We wanted three different symbols to appear on each needle. Technically, this is impossible, but you can create three needles that are offset by a very small amount so that the three needles look like one. This is the reason for the AMNTS=AMNTS+.001; and AMNTS=AMNTS+.002; statements in the program |
7 | ||
| 37 | Use of the Where Clause in SAS 6.07 | Robert Zdanky | The talk will explain to the beginning user how using a WHERE clause with indexing will save CPU time. By using a where clause the SAS user does not need to use a DATA STEP to select subsets. The paper will also talk about WHERE clause operators such as: Between And, Contains, Is Null Is Missing, Like Same and |
cpu time, proc step, where statement, proc means | 4 | |
| 38 | Using and Understanding SAS Formats | Howard Levine | proc step, proc format, format statement, put statement, dataset, proc print, char. | 7 | ||
| 39 | Using PROC IML to do Matrix Balancing | Carol Alderman | proc iml, proc step | 6 | ||
| 40 | Using PROC TABULATE - A Review of the Basics and A Look at Using This Procedure With Multiple Response Data | Catherine M. Cerone | FROC TABULATE allows the user a good deal of flexibility in generating tables of percentages or frequencies. This flexibility allows to correctly calculate percentages on multiple response data. A multiple response question is one for which a panelist may respond with more than one response. Therefore, care must be taken when percentages are calculated on these questions. This paper will begin with some basic information about using PROC TABULATE, take a look at some commonly used options and then discuss how to define percentages in FROC TABULATE to make an analysis of multiple response data more meaningful. Qyerv iew FRoe TABULATE is one of the descrip~ive procedures available in the SAS system. It allows you to summarize data in tables with one, two, or three dimensions. A one dimensional table would contain a column of data representing the values of a specified variable |
proc tabulate, proc step, proc freq | 10 | |
| 41 | Using Public-Use Microdata Samples With SAS | Warren A. Brown, Lisa King |
sample, sample size, proc freq, proc sql | 5 | ||
| 42 | Using SAS Macro Facilities to Simplify A Large Multi-Event Statistical Analysis | Douglas P. DeYoung | macro variable, macro conditional, macro definition, anova, sample, repeated measures, outlier, data science, proc freq, proc step, data cleaning, macro loop, proc genmod | 6 | ||
| 43 | Using SAS to Maintain Historical Databases of Research Project Information | Susanne L. Daood, Randy Stick |
batch job, data science | 7 | ||
| 44 | Using SAS to Process TIGER Line Files: A User's Viewpint | Hendrik M. Meij | proc step, dataset, libname statement, proc gmap | 8 | ||
| 45 | Using the SAS System for Remote Data Access and Distributed Computing | John McIntyre | 4 | |||
| 46 | Writing SAS Code Behind The Scenes: A Conversational Macro Example | Deb Cassidy | Deb Cassidy, Trilogy Consulting Corporation ADVANTAGESillISADVANTAGES Conversational macros provide a way for a non SAS user to "write" BAS code when only base BAS is available. This paper will give you some advantages/disadvantages of this method as well as how to write the code | macro variable, macro put, macro loop, put statement, %if-%then-%else, if-then-else, macro definition | 6 |
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