MWSUG 2000 Papers - Index

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

#	Title ×	Authors ×	Abstract ×	Keywords ×	Pages
1	Advanced DATA Step Techniques	Neil H. Howard	Understanding the intricacies of the `DATA STEP` can make all the difference In your SAS programming. Many other conference proceedings contain tutorials on the following `DATA STEP` topics: " arrays, " SAS date and time functions, " debugging, " functions and formats, " efficiency, " INPUT statement. This tutorial focuses on the more advanced techniques that capitalize on the power of the `DATA STEP` and working with (and around) the default actions. Topics Include: " compile versus execution time activities; " organizing your data to maximize execution; " data defaults, data conversions; " missing values, formatting values; " ordering variables; " functions for: editing data, assigning values, shortening expressions performing table lookup; " data management; " effectively creating SAS data sets; " the logic ofthe MERGE; " efficiency techniques. 'Real world' examples are presented to illustrate each topic	proc step, proc format, dataset, missing value, lookup, put statement, proc print, proc sort, update statement, if-then-else, raw data, input statement, character functions	10
2	Anyone Can Learn PROC TABULATE, V2.0	Lauren E. Haworth	SAS Software provides hundreds of ways you can ana lyze your data. You can use the `DATA STEP` to slice and dice your data, and there are dozens of procedures that will process your data and produce all kinds of statistics. But odds are that no matter how you organize and analyze your data, you'll end up producing a report in the fonn of a table. This is why every SAS user needs to know how to use `PROC TABULATE`. While TABULATE doesn't do anything that you can't do with other PROCs, the payoff is in the output. TABULATE computes a variety of sta tistics, and it neatly packages the results in a single table. Unfortunately, TABULATE has gotten a bad rap as being a difficult procedure to learn. This paper will prove that if you take things step by step, anyone can learn `PROC`	proc tabulate, proc step, ods html	9
3	Building a Better Data Entry Applciation Using PROC FSEDIT	Derek P. Morgan, Michael A. Province	It was once said that, "If you build a better mousetrap, the world will beat a path to your door." However, for data entry system programmers, "a better mousetrap" is designed to keep people away from our doors. We don't want visits from users with questions about using the system, nor from analysts who want to know why there are SOO-pound children sprinkled liberally through the database. Finally, we definitely don't want administrators and supervisors to come knocking, demanding to know why the users and analysts are calling them. This advanced tutorial will cover items beyond the basics of the `FSEDIT` procedure with the goal of building a better data entry system. Familiarity with SCl is helpful. The topics to be covered Include: Screen Ergonomics (use of color and placement of items) The difference between the FSEINIT section and the INIT section Cursor control-when NOT to use the defaults Screen variables vs	where statement, sample, proc step, data cleaning, character variable, proc format	10
4	Building a Low Cost SAS Data Warehouse on NT Workstation	Zhuan (John) Xu	More and more companies now understand the benefit of data warehousing. However, a typical warehouse project uses expensive hardware and software. And it usually requires a team of developers. As the PC hardware becomes much more powerful and cheaper, and as the NT operating system becomes more stable, It is now feasible to develop a small scale data warehouse project on PC platform. Since SASlBase provides the much functionality needed for a warehouse project it is a good fit for such project. This paper presents a case study of the Medicare Data Warehouse at WeliMark Blue Cross Blue Shield of Iowa. It contains the database, a front end for data extraction, a tool for data analysis, and an application designed to solve a special business issue. This paper will discuss a few issues related to such project and some techniques . used	extract, proc sql, excel	4
5	Creating HTML Output with Output Delivery System	Kirk Paul Lafler	Have you ever wanted to turn your basic monospace SAS· Listing output into formatted output viewable by all on the web? If the answer is 'yes", then this workshop 'Will show you how to use the Output Delivery System (`ODS`) to create HTML output by formatting output in Hypertext Markup Language (HTML). `ODS` controls the formatting of all procedure and `DATA STEP` output and provides great flexibility when working 'With output You will learn how to use `ODS` to create an HTML file, a table of contents, a table of pages, and a frame file. This workshop is intended for SAS Software users 'With some PC-SAS and HTML experience. Before attending this workshop, you should be comfortable using PC-SAS, an Internet browser such as Internet Explorer or Netscape, and HTML	sas output, output delivery system, file statement, ods html	3
6	Creating Maps in SAS/GRAPH	Jeffery D. Gilbert	This paper will give an introduction to creating graphs using the `PROC GMAP` procedure in `SAS/GRAPH`. Instruction will be given to create basic maps using map tables provided by The SAS Institute. In addition, some special topics will be discussed, including `SAS/GRAPH` global statements and the annotate facility when using `PROC GMAP`. Maps in The SAS System Maps can be used for many kinds of reports, and are very useful for visually describing data across a geography, such as the United States. The SAS System has three basic types of maps: 1) . The CHOROPLETH (or CHORO for short) map, which displays data on a flat map. 2) The PRISM, which shows maps three dimensionally, and can give a greater feel for differences and between states/regions. 3) The SURFACE map. which shows mOre general areas and can be useful for picking out clusters. A basic CHORO map that many people might want to produce looks like the below picture: -'	proc step, proc gmap	5
7	Developing SAS Application Using Microsoft Excel	Zhuan (John) Xu	The SAS system is a powerful tool for data and statistical analysis. SAS macro variables are introduced as parameters to a SAS program. This allows users familiar with the SAS system to perform various analyses. Many times, a user friendly graphic user interface is desirable for such SAS programs. Additionally, as analysts often load the result from SAS program into spreadsheet such as MS `EXCEL` for further analysis and presentation, it is helpful to automate the process. This paper describes details of using MS `EXCEL` to create a GUI. The GUI will allow users to enter or select parameters and generate corresponding SAS macro variables. It will then run the SAS program and produce SAS output in the same `EXCEL` file. In this way, an SAS application is completely embedded inside a spreadsheet. INTRODUCTIOt,j This paper is a tutorial on integrating SAS system with MS `EXCEL`. We develop a SAS program and create some macro variables as parameters	excel, macro variable, macro definition, dataset, class variable	5
8	Efficient SAS Programming Techniques	Kirk Paul Lafler	As SAS" Software becomes increasingly more popular, guidelines for its efficient use are critical. Areas deserving special consideration include program execution, 1/0, disk space, and program maintenance. A collection of techniques and sample code are presented to illustrate numerous practical techniques for gaining efficiency while using SAS Software	cpu time, drop statement, dataset, proc sql	6
9	Extending the Data Warehouse: An Introduction to OLE DB	S. David Riba	Now that you have your data warehoused, how do you share that infonnation with others who need access to it? SA~ software provides a variety of tools to access and retrieve data from multidimensional databases (MDDBs). However, MDDBs are not accessible to non-SAS users in your organization. Until now. Starting with Version 7 of the SAS System, OLE DB can be used to access the infonnation stored in SAS MDDBs and eFO Vision FOBs. OLE DB can be used to access the infonnation stored in ANY multidimensional database that is OLE DB compliant. Starting with the release of Windows 2000 Professional, OLE DB will be installed as part of the operating system. In Microsoft Office 2000, all member applications will be OLE DB consumers. The same is true for Lotus SmartSulte member applications	proc sql, data mining, dataset, structured data, excel	9
10	Getting Started with SAS/AF - Frame Your Base SAS Programs	Andrew S. Rosenbaum	Some programs are created with hard-coded values that need to be changed on a regular basis. This amounts to rewriting the program every time a change is made to one of the parameters. For example, a report of hours worked by employees for certain days. If the person requesting the report is not versed in the ways of SAS System programming, then a programmer must go into the program, find the parameters to be changad, make the changes, and run the program. Instead, the program cen be written with variables in place of tha hard-codad values. Any user can change the variables at run-time by way of a graphical user interface (GUI) also known as a FRAME. This frees the programmer to create programs instead of running them for others. This procedure is sometimes known as 'wrapping'	sas base, data step, macro variable, error message	5
11	Graphs In a Minute	Jeff Carter	SAS Software offers multiple ways of producing attractive graphics quickly wfth simple user interlaces. This paper focuses on two of them: the Graph-N-Go application in Version 8 and the Graph tasks in Enterprise Guide Version 1.0. With these applications, you can visualize your data quickly as different chart and plot types and Include your results into your documents and reports	sas enterprise guide, bar chart	5
12	How to Use the DATA Step Debugger	S. David Riba	All SASe programmers, no matter if they are beginners or experienced gurus, share the need to debug their programs. Many techniques have been suggested over the years to solve the problem of debugging `DATA STEP` logic. Until now SAS programmers have never been able to interactively watch the `DATA STEP` execute and debug their logic as it executes. Introduced in Release 6.11 of SAS, the `DATA STEP` Debugger is part of Base SAS softWare. It is an interactive tool that allows the SAS user the ability to watch and control `DATA STEP` execution. The `DATA STEP` Debugger can be used to: .:. watch program logic execute .:. examine variable values as they change .:. repeat program statements .) jump to other sections of the `DATA STEP` .:. modify DO loops interactively .:. test for "dead" code .:. give commands * :- observe the resuHs interactively The `DATA STEP` Debugger is a very useful tool, whether you are a Beginning SAS Programmer or a SAS veteran	sas log, sas base, options statement, if-then-else, end	9
13	HTML for the SAS Programmer	Lauren E. Haworth	With more and more output being delivered via the Internet, a little knowledge ofHTML can go a long way toward improving the appearance of your output. This paper introduces some simple HTML coding techniques that are useful for SAS programmers. The paper will show how your SAS output is converted into HTML, and dem onstrate HTML tricks that you can use in your SAS code to dress up your SAS HTML output. All of the examples can be produced using either SAS version 6 or versions 7-8.	ods html, sas output, footnote statement, proc print, proc step	8
14	Implementing Technology Based Quality Solutions	Robert Noakes		kyc, correlation	9
15	Indexing and Compressing SAS Data Sets: How, Why, and Why Not	Andrew H. Karp		character variable, dataset, where statement, numeric variable, proc step, length statement	5
16	Input File Cleaning and Screening Using Base SAS	Mike D. Tangedal	Building a thorough logic table noting all screening and quality checks to be put in place for data input files of a known structure can pay great dividends. Using Base SAS and the logic in the table, this macro serves to help build a detailed quality enhancement tool with minimal effort. The key is to apply generalizations in terms of standard SAS code based on SUlllllllU'Y category eodes. Format tables as well as capturing output from `PROC FREQ` and `PROC MEANS` is also used. The result is a input file SUlllllllU'Y table listing each variable aIong with the number of missing observations and sUlllllllU'Y infonnation such as range, list of values, and Dumber of values equal to zero. The result of this macro is a data set containing the input fde infonnation plus flags set by the logic table. Also created are reports sbowing examples of anomalies in the input file and frequency reports of categorical variables	proc step, macro definition, if-then-else, data cleaning, proc freq, temporary array, numeric variable	7
17	Making the Transistion from College to Industry	Brian K. Varney	Most people who end up as SASe programmers do so coming from a statistics or computer sclence program. Many times neither does a good enough job at teaching the fundamentals of SAS programming. Computer sclence programs typically teach lower IeYellanguages such as C++ and statistics programs focus more on ataIiatical theoIy and analysis. The introduction of SAS programming gets left up to Industry. OVer the past few years more and more c:oIleges have been Implementing SAS progRlmming courses which is helping tremendously	data step, decimal, character variable, numeric variable, macro facility	3
18	Managing Independent Consultants - An Oxymoron?	Neil H. Howard, Michelle Gayari		proc step, data cleaning, missing value, proc print, put statement, sas log, proc contents, proc freq, cpu time	9
19	Merges and Joins	Timothy J. Harrington	This paper discusses methods of joining SAS data sets. The different methods and the reasons for choosing a particular method of joining are contrasted and compared. Potential problems and limitations when joining data sets are also discussed. The need to combine data sets constantly arises during software development, as does the need to validate and test new code. There are two basic types of jOin, vertical, and horizontal. Vertical joining is appending one data set to another, whereas horizontal joining Is using one or more key variables to combine different observations. Vertical Joining A good example of vertical joining is adding to a data set in time sequence, for example, adding February's sales data to January's sales data to give a year-to date data set. Providing both data sets have the same variables and all the variables have the same attributes such as data type, length, and label, there is no problem	proc step, proc sql, missing value, order by, create table, inner join, full join, raw data, right join, by group processing, proc sort, where statement, coalesce function	6
20	Pharmaceutical Application of SAS Enterprise Miner	Thomas H. Burger, Jerry E. Plaatje, John M. LaBore, James K. Malone	Competitive advantage requires rapid formation of soWid inferences for product decisions. As information repositories, warehouses store teradata for decision support. Strategic use of this data requires techniques proven for information delivery. Mining reves1s relationships for knowledge formation through methodological data selection, exploration and modeling. A structured process ensures conformance to business assumptions for reliable interpretation. To illustrate, we discuss data mining in pharmaceuties1 research	data mining, hypothesis testing	5
21	Positioning SAS for Corporate Effectiveness	John M. LaBore, Thomas H. Burger	Accelerated research and development has increased industIy reliance on Information Technology (IT). Biopharmal:eutical IT divisions increasingly require an infrastructure capable of providing global enterprise-wide business solutions. However, when the application of IT innovation to business solutions occurs at an insufficient rate, business needs go unfulfilled. Of particular importance to accelerating research is the implementation of application software for decision making. SAS software provides powerful tools for data warehousing, decision support and presentation, but their effectiveness is directly proportional to an understanding of business issues and how 8AS can solve them. A strategy for the integration of these tools into the business streamlines and accelerates critical processes. IDtroduc:tioD. Competitiveness in the biophannacentical industIy increasingly requires globalization. Research at this scale	data migration, clinical research	6
22	Post-Processing SAS/GRAPH generated CGM's to Eliminate Text String Bugs	Gerhardt Pohl	Gerhardt Pohl, Eli Lilly and Company, Indianapolis, IN	macro definition, proc gplot	7
23	Power Indexing: A Guide to Using Indexes Effectively in Nashville Releases	Diane Olson	In Version 6 of the SAS System software, there were performance problems with some index features. This paper addresses how thdse problems heve been resolved in the Nashvnle releases (Version 7 end leter releases). It also supplies guidelines to help you decide when indexes will benefit your application and increase the performance of your SAS programs. Ouestions answered in this paper include: [J What are indexes? [J How do I creata an index? [J What are the benefits of an index and when does the SAS System use indexes to access data? [J What additional resources do indexes use? [J What are the index improvements in Nashville releases? > Centiles > More User Control > `APPEND` Procedure > Expended WHERE Optimization > MSGlEVEl=1 [J When will an index help me the most? [J How can I tune my use of Indexes?	dataset, index, proc append, proc step, by group processing, set statement	5
24	Removing Slag to Get the Ore: Preparing Data for Mining	Thomas H. Burger, Jerry E. Plaatje, John M. LaBore	Competitive advantage requires rapid fonnation of sound inferences for knowledge discovery. Key to information delivery is data analysis and presentation. Warehousing enables storage of teradata for decision support; strategic use of this data requires proven techniques. Mining fosters disclosure of relationships through exploration and modeling. However, preliminary data preparation is essential to ensure it is performed upon data in its final desired form. Typically, steps are first required for data assimilation to identify and remove errors. Standard methods for data management increase reliability and speed this process. We discuss issues associated with preparation of data for mining	data governance, data wrangling, hypothesis testing, character functions, data mining, proc freq, proc step	4
25	Ring Charts	David J. Corliss	Ring Charts are presented as a new, graphical technique for analyzing complex relationships between tables in a relational database. Charts are constructed in the SAS System by creating an Annotate dataset. `PROC GSLIDE` is then used to produce graphical output. Ring Charts provide the frequency of table joins in a visual format, allowing the system analyst to identify important characteristics. These include hierarchies, inefficient operations, and system constraints	data merging, proc step, relational database	7
26	SAS MACRO Basics and Fundamentals	Timothy J. Harrington	This paper introduces and discusses the SAS MACRO language for new SAS Programmers, or those with some prior SAS MACRO experience. This paper also explains the role of SAS Macro code in the SAS System compilation and execution phases and how SAS MACRO and the Base SAS System may be used together to write more efficient code and tackle specific programming tasks. The major SAS MACRO topics and common functions are illustrated, with examples, as well as common problems encountered, and their solutions, when using the SAS MACRO language. The role of SA8 MACRO The SAS Macro compiler is a pre-compiler, which, with only a few exceptions, resolves SAS Macro code before the Base SAS (or SAS SCl) code is compiled. The basic sequence of events is thus: The SAS MACRO language has two types of code (1) Invocation Statements, preceded by a percent (%) sign and (2) Macro Variables, preceded by an ampersand (&)	macro variable, macro definition, sas base, macro facility, variable, macro quoting function, %if-%then-%else, macro put, proc step, clinical trial, clinical data, macro function, call symput, character variable, proc print, proc sql, where statement, macro loop, macro flow control	10
27	The Development of the Ohio State Highway Patrol's Cadet Allocation Model	Gary M. Macklis	In July 1999. The Ohio State Highway Patrol decided to modify the method it used to assign newly graduated cadets to the 54 Patrol posts located throughout the state. To this end, the Research and Development Unit was asked to develop a computer-based model to allocate staff using various measures of trooper activity and state demographics. Approximately 30 activity and demographic measures were gathered such as the number of crashes investigated per post and the number of licensed drivers In a post's jurisdiction. Needing a powerful stetistical program, Research staff used the SAS System for PCs to perform the statistical work in the creation of the Cadet Allocation Model (CAM), a linear regression model. By providing several different model selection options, the `REG` procedure in SASISTA r made choosing the final set of variables to be included in the model in much easier	regression analysis, multiple regression	3
28	The SAS System Electronic Mail Interface: A Case Study	Derek P. Morgan	The 1999 International Genetic Epidemiology Society meeting used software developed with the SAS System for registration and abstract management. Given the intemational nature of the presenters and attendees, however, conducting the routine business associated with these tasks by telephone or postal service would quickly get expensive. To reduce administrative costs, the organizers wanted to use electronic mail as the primary	put statement, set statement	3
29	The Ugliest Data I've Ever Met	Derek P. Morgan	Data management frequently involves interesting ways of doing things with the SASe System. Sometimes, "inter esting" becomes another way of saying "messy", especially when it comes to processing files from outside of your department. This paper will detail the code used to transform raw data we received into raw data that we could use. At first glance, flat file-ta-flat file translation wouldn't seem to be a problem. However, this is a list of the programming methods necessary to perform this par ticular transformation: Automation of a process using SAS System macros Reading from and writing to multiple files with a single `DATA STEP` Using the SAS System to write its own code ·on the fly" Adding sequence numbers for new records in a data set * "Arrays· of SAS System macro variables The code in this real-life production application will be used to illustrate each of these methods, and to show the reasoning behind their use	dataset, flat file, macro variable, proc step, put statement, input statement	5
30	The Ultimate Match Merge: Hiring the Best SAS Programmers	Neil H. Howard		sas programmer, data cleaning	10
31	Using Metadata for Data Driven Programming	Brian K. Varney	Creatfng dynamic, data driven proglllms is a very powerful tool. Often we can use the metadata or the project data it&eIf to help write our programs. This paper will Introduce some of the concepts related to writing SAS· programs which will g_rate pieces of SAS codlI in a data driven manner. Parts of the SAS language used in this discussion Include the following: 1. macro call routines (call execute, call symput) 2. PROCSQl 3. SAS Dictionary Tables Programming techniques used In this dlscusalon Include the following: 1. using saquential macro variables with macro do loops 2. generating SAS code, writing It to an extemaIllle, and 'II.including it at a later time 3. generating and executing SAS code using call execute 4. checking If a data set exists 5. checking If a variable exists In a data set 6. checking If a data set is empty 7. using subqueries for multiple data set subselling	macro variable, proc sql, proc step, call execute, dictionary tables, macro loop	4

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