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BUGSMWSUG 2003 Papers - Index
38 papers. Source: MWSUG (Midwest SAS Users Group) conference proceedings.
| # | Title× | Authors× | Abstract× | Keywords× | Extras | Pages |
|---|---|---|---|---|---|---|
| 1 | 44 Tricks with the 4mat Procedure | Ben Cochran | Actually, there probably are not a total of 44 tricks that one can do with the FORMAT procedure. The number was chosen purely for the purposes of alliteration. However, there are some fairly powerful things one can do with this procedure, and this paper serves as a gentle |
proc step, proc format, format statement, proc print, proc freq | 3 | |
| 2 | A Gentle Introduction to SAS/GRAPH Software | Ben Cochran | The power and flexibility of SAS/GRAPH software enables the user to produce high quality graphs, charts, and maps. With all this strength and flexibility, the new user is sometimes overwhelmed and discouraged from using these powerful tools. However, learning how to use the tools of SAS/GRAPH can be a pleasant experience. This paper introduces several ways to generate graphical representations of your data. Starting with the importance of understanding their data, users are lead in a step by step process that ends with the generation of high quality plots and graphs. Let us begin. Step 1: Understanding Your Data. Is some data more appropriate for generating graphical reports than other data? What data is most appropriate for plots and graphs? The first data set to be examined is the SASUSER.RETAIL table. Retail aalesin milliol1sof $ 220 257 258 |
proc gchart, proc step, bar chart, proc gplot | 5 | |
| 3 | A Macro Program for Displayin T-test Results | Brent L. Baxter | The Student's t-test is one of the most common statistical tests used to compare the means (or proportions) of two independent groups. However, the standard SAS output from PROC TTEST proves to be cumbersome for identifying and displaying the most meaningful |
proc step, proc print, proc ttest, standard deviation, macro variable, sample, macro definition | 12 | |
| 4 | A Peek at PROC DOCUMENT | Andrew H. Karp | The DOCUMENT destination, added to SAS 9 Software, is a significant enhancement to the Output Delivery System that offers new capabilities to work with "objects" created by the interplay of SAS Procedure and ODS functionalities. By learning how to use this new feature of the SAS System you can work even more efficiently with Procedure-generated output. Essential Concepts The Output Delivery System has revolutionized the way SAS users work with Procedure-generated output. With the implementation of ODS as a production feature of Version 8 of the SAS System, users now have a vast array of tools with which to modify the appearance, as well as the "output destination" of their Procedure output. One "missing link," with ODS in Version 8 was, however, the ability to store and subsequently "re-use" output objects without having to re-run the Procedure. To fix ideas, let's review how ODS "works" within the SAS System |
proc step, sas 9, proc report, output delivery system, sas base | 2 | |
| 5 | A Table-Driven ODS Macro | Diane E. Brown | Tired of coding ODS statements and SAS output procedures for every report you write and having redundant or similar code everywhere? This paper will present a plan to reuse SAS output source code using a SAS table to drive the process and macros to execute the process. A complete review of the table design and content, and the source code will be provided. User controls available in the macro include: 1) variables to output, 2) the output styles; pdf, html, txt, SAS, EXCEL, rtf, mdb, etc., 3) ODS style, 4) titles and footnotes, and 5) SAS output procedure. This routine also addresses the common problem situations: 1) Zero observations and no report output is generated, and 2) Too many observations and output is too large |
macro variable, macro loop, macro definition, %if-%then-%else, proc step, sas output, dataset, proc freq, macro quoting function, stored macro, ods rtf | 8 | |
| 6 | Accelerating Performance of SAS Applications via Rapid Extraction and Multiprocessing | John M. LaBore, Fred R. Forst |
All large commercial operations generally face the same problems: massive amounts of data; hardware/software constraints; and tight deadlines to generate analyses and reports. Handling these situations has always been a SAS software strongpoint. However, even within SAS, determining the best (i.e., fastest) method is not always easy, since SAS typically provides multiple ways to accomplish the same task. This is further compUcated by the common situation within companies of having multiple hardware platforms, muHiple datasources, and a vast array of reporting requirements and needs. Today's rapid rate of mergers and acquisijions, the creation of joint ventures, and the evolution of all types of working alliances/collaborations further increase the likelihood of such complex computing environments. In this paper, we examine real-time performance across a variety of hosts, dients, and datasources using different approaches to extract and process data | proc step, elapsed time, proc copy, proc print | 8 | |
| 7 | Addressing 21 CFR Part 11 Concerns with Execution and Repository Control | Curt Wehrley, Donald L Penix Jr., Wing Lam |
The Code of Federal Regulations (CFR) TIlle 21 Part 11 represents the FDA's effort to stimulate the use of information technology to achieve improved efficiencies in new drug development, submission, review and approval. While the federal government has opted to provide enterprises with some flexibility as they develop their approaches to compliance, the ruling actually represents another Y2K-type system upgrade effort for the Pharmaceutical industry. Many companies have years of effort and millions of dollars invested in existing software and hardware for clinical trials, and Part 11 touches nearly every system. Achieving compliance, while making the best use of existing systems, represents a major challenge for most enterprises. This paper will provide a high-level view of a solution to this compliance challenge | life sciences, audit trail, 21 cfr part 11, data science | 8 | |
| 8 | Advanced Macro Topics | Steven J. First | The SAS macro language conttnues to be an integral part of 1he SAS system, and can be a wonderful tool or an overcomprlCaled SOlution. This paper will be of interest to macro users that would like to more fuRy understand the macro system. This paper will discuss the following topics: 1. 2. 3. 4. 5- 6. 7. 8. 9. Macro date structures and timing l.ocaI and Global referencing environments Quoting Macro and date st9!l functions and call rouIines Debugging and 1racing techniques AutoCall facilities Design considerations Alternatives to SAS macros Changes and enhancements with Version 7 and 8 | macro variable, macro facility, data step, proc step, call symput, macro put, macro definition, proc print, macro function, put statement, run, symbol table, macro call, macro quoting function, stored macro, macro loop, %if-%then-%else | 8 | |
| 9 | Beginning Macros | Destiny Corporation (a company) | macro variable, symbol table, put statement, proc step, automatic macro variable, macro put, keyword parameter, macro parameter, %macro parameters, proc print, missing value, macro definition, macro quoting function, global symbol table, macro facility, title statement, macro call, options statement | 14 | ||
| 10 | Breaking Up Is Hard To Do! Understanding the CGM Specification | Michael P. Bramley | While the latest versions of The SAS System have included significant advances in document selection, organization, and publication-ready output, the drivers in the SAS/GRAPH software have also been updated. One such update is how these drivers implement the Computer Graphics Metafile (CGM) specification. This implementation can adversely affect SAS programs that output multiple graphs into one Graphics Stream File, with the intention of spfitting it up on a target system, say for use In word processing systems. This article includes a brief history of the CGM specification, a gentle introduction to the workings of the CGM specification, and how the implementation of the CGM specifICation differs between versions of SAS software that result in good old 'gotchas'. Wrth this necessary ground covered, an effiCient single-pass algorithm is presented that converts any SAS/GRAPH software created CGM file containing k graphs into k files, where the kg, file contains the kg, graph |
macro variable, macro function, %if-%then-%else, sysrc, macro definition, _eof_, macro loop | 6 | |
| 11 | Building Drill-Down SAS Applications | Kirk Paul Lafler, Charles E. Shipp |
output delivery system, proc step, ods html, proc univariate, ods pdf | 4 | ||
| 12 | Changes & Enhancements to Version 9 | Dana Rafiee, Destiny Corporation (a company) |
proc step, sas log, sas management console, hash table, excel, options statement, libname statement, macro variable, ods pdf, dataset, proc export, proc tabulate | 17 | ||
| 13 | Data Management: Building a Dynamic Application | Arthur L. Carpenter, Richard O. Smith |
Data Management: Building a Dynamic Application Arthur L. Carpenter, Data Explorations Richard o. Smith, Data Explorations You have written a series of interesting and often complex SAS programs that perform a variety of data entry operations, data checks, exception reporting, statistical analyses, and summary reporting. Since the next study is somewhat similar to the last one, you are planning to build another set of programs based on (cannibalized from) the ones that you just used. We have been there before, but STOP. Wouldn't you rather build and validate the programs just once? The solution lies in building and using data dictionaries that act as control files. These control files are in turn used to create a series of SAS macro variables that are available as arrays to each of the various programs. All project, data set, and variable specific information is stored in the macro variables and hence never in the programs themselves | macro variable, macro loop, do loop, variable list, %if-%then-%else, call symput, macro definition, label statement | 12 | |
| 14 | Easy, Elegant, and Effective SAS Graphs: Inform and Influence with Your Data | LeRoy Bessler | Are you an existing SAS/GRAJ'H user who would like to create charts that are more communication-eftective? Or are you one ofthose software users who process their data with the SAS System, but then export the output to some other tool to graph it? This tutorial assumes no prior knowledge ofSAS/GRAPH. It cuts through all the documentation and bypasses the problem of "Options OveiChoice" to empower you to make elegant and effective pie charts, bar charts, and trend charts-to get them right from the start. You will come away with widely applicable design principles and examples, and with supporting code that you can understand, and can point at your own data when you get bnck to the office. SASIGRAPH can be easy, and, based on good design and good examples, communication-effective use of SAS/GRAPH gives you The Power to Show: to inform and intluence, to reveal and persuade, with charts and data |
bar chart, proc step, vertical bar chart, horizontal bar chart, proc gchart, proc sort, output delivery system, class variable, macro definition | 10 | |
| 15 | From the Mainframe to the Sun to the World | Carmen Williams, Rose Keeley, Carol Drechsel |
Carmen Williams Rose Keeley Carol Drechsel University of North Dakota July 7,2003 The goal was to automate the way we generate and report our daily student registration activity, while still utilizing the mainframe data and programs along with the UNIX and PC environment. This session talks about the steps we took to accomplish this goal. That is, to install and utilize SAS/INTRNET in order to automatically generate and post web HTML reports from the mainframe. The SAS/INTRNET project was implemented through the Higher Education Computer Network. The principle users of the SAS products are located at the University of North Dakota (UNO) and North Dakota State University (NDSU). At the campuses we currently use an IBM mainframe (OS390) system, so steps involved the coordination of activities from the mainframe to the (Sun) server |
sas consultant, sas output | 5 | |
| 16 | Getting More For Less: A Few SAS Programming Efficiency Issues | Arthur L. Carpenter | Arthur L. Carpenter California Occidental Consultants The old saying goes "If there is one way to do it in SAS@, there are three ways to do it." Inevitably, when this is said in a group, there will be someone (probably a Quality Partner) who will chime in with "And I will show you a fourth way." It is of course wonderful to be working with a language that has the flexibility of multiple programming solutions, but this flexibility can come with a price. Very often the most obvious coding solution turns out not to be the most efficient one. It is not unusual to fmd programs written by programmers with a view to the end result, but with no understanding of the process of the best way of getting there. If there are multiple solutions to a programming problem, which solution is the correct one? And then the bigger question becomes, 'Does it make a difference?' | proc step, if-then-else, cpu time, proc sql, retain, subsetting if | 7 | |
| 17 | Intemediate Macros | Destiny Corporation (a company) | macro variable, symbol table, call symput, put statement, global symbol table, local symbol table, macro put, data step, proc step, character variable, sas log, work library, macro loop, input statement, macro definition, if-then-else | 12 | ||
| 18 | Macro Quoting Functions, Other Special Character Masking Tools, and How To Use Them | Arthur L. Carpenter | Quoting functions allow the user to pass macro arguments while selectively removing the special meaning from characters such as &, %, ;, " and ". Most of these functions are not commonly used and are even less commonly understood. Although they are powerful and can even be necessary, usually programming solutions are available that do not require the use of the quoting functions. When are quoting functions needed? When needed how are they used? Which one should be selected? This paper will discuss when to use and when to avoid quoting functions. In addition the discussion will include solutions that avoid the use of quoting functions. Fortunately there are several ways to mask special characters within the macro language. These include quoting functions, %DO blocks, restructuring of statements, and the character mask (%) | macro variable, macro quoting function, macro facility, macro loop, macro put, macro function, proc print, %if-%then-%else, proc step, macro definition | 8 | |
| 19 | Missing observations: Identification and resolutions using the SAS System | Doug Moore, Tahereh Nourbakhsh |
This paper will discuss identification of cases where missing values or missing records in a data set either create interpretation problems or generate results that do not meet the requirements of the report we are asked to produce. By missing; we mean situations where no value is provided for a variable in one or more records or when all variables corresponding to a key variable are missing in which case the record would usually not show up in the data set. Resolutions to address the problems identified will be provided | missing value, adverse events, raw data | 14 | |
| 20 | Numerical Representation and Rank-Based Statistics: A Cautionary Tale | K. D. Stromberg, T. L. Fox |
Many rank-based nonparametric statistics such as the Wilcoxon Signed Rank Test or the Wilcoxon Rank Sum Test are computed by ranking the data and assigning any tied values the average rank. Test statistics and p-values are then calculated from the ranked data. A potential problem may arise during the calculation of these statistics since computers can't store some real numbers with infinite precision. Numbers that can't be represented in computer memory exactly are stored with a very small roundoff error. Thus, numbers that appear to be identical in a dataset or on the screen may be stored by the computer with slight differences. By default the SAS system uses the full stored precision of a number to determine whether two values are tied when assigning ranks in both PROCs UNIV ARlATE and NP ARl WAY | proc step, decimal, proc rank, rank test, null hypothesis | 10 | |
| 21 | ODS (Output Delivery System) | Destiny Corporation (a company) | proc step, output delivery system, ods html, proc contents, ods listing, proc print, sas output | 13 | ||
| 22 | Output Delivery Goes Web | Kirk Paul Lafler | In an age of Internet frenzy, output delivery is experiencing incredible interest around the globe. The explosion of Internet technologies, especially electronic delivery of data, is on the rise. As digital commerce forces fundamental changes in the nature of business, IT is at the center of these changes. Many organizations are moving toward a customer self-service center model, where information access will be key to survival. As the growth and popularity of the Web surges to unprecedented levels, SAS users are beginning to look for ways to transform basic monospace output into an electronic world of glitz and color. This advanced tutorial will show attendees how to convert tired and old output listings into beautiful Web pages, combine output results, create PDF output, change Web page labels, build drill-down Web applications, and perform a variety of output customizations | ods html, sas output, proc univariate, file statement, proc step, output delivery system, ods pdf, proc print | 7 | |
| 23 | Parameter Estimation of a Negative Binomial for the By-product of the Gringard Reaction | Ling Huang, Paul W. Johnson |
The Oringard reaction is a common undergraduate organic laboratory experiment At Sacramento City College this reaction is taught within the organic chemistry laboratory to students. It is taught to illustrate an example of organic synthesis. The product produced by way of the reaction is 2-phenyl- 2-propanoI. Occasionally there is a by-product product. This is phenylbenzene. A negative binomial model can be used since the average by-product is unlikely for the Oringard reaction (Le., this is the case when no by-product is a common occurrence). The parameters of the negative binomial are estimated using the method of moments. An improved estimate of the sample mean is obtained from use of the bootstrap. The SAS macros listed below are available from the authors at http://pages.prodigy.netljohnsonpl2Jgringard.htrnl. The macros (01 and 02) require base SAS (SAS, 1990) and SAS/STAT (SAS, 1993) software to run |
bootstrap, confidence interval, sample, binomial distribution, negative binomial regression, proc step, proc sort, macro definition | 4 | |
| 24 | Primary Care Physician Portal: Identifying, Managing and Monitoring Patient Care | Priscilla Van Grevenhof, Ahmed S. Rahman, Rose Cabanela |
excel, data warehouse | 6 | ||
| 25 | PROC TABULATE Basics | Destiny Corporation (a company) | proc step, proc tabulate | 5 | ||
| 26 | SQL Basics | Destiny Corporation (a company) | group by, proc step, select, proc sql, where statement, order by, dataset, data step, error message, sas programming, proc means | 17 | ||
| 27 | The Power of Paint: Effective Color Communication with ODS, SAS, and SAS/GRAPH | LeRoy Bessler | This tutorial discusses color, crucial color concerns dependent on output destination (especially the web), and design for effective visual commWlicution (not decoration) with color. SAS 8.2 is used. The intended audience is all levels of SAS users, and the design principles are actually software-independent Introdnction Any information or iIlustrstions developed for the slide presentation between date of submission of this paper for publication (July) and the conference date will be available via an emailable zip file of the slides. If you bave comments or questions, or suggestions on wbat to cover in a future edition of this paper, please send them. I regret that I cannot provide precise bibliographic citations for the research study results cited below, nor for the the remarks attributed to Jan White, Michael Turton, and Aaron Marcus. Such information is drawn from notes taken from reading and listening about ten years ago | sample, proc step | 5 | |
| 28 | The Power of Pictures: Using Image Files with ODS, SAS, and SAS/GRAPH | LeRoy Bessler | You might want to use a logo. You may have images created with a digital camera. Hardcopy photos or illustrations, or even a 3D object, can be converted to image files with a scanner. There are stock photos and clip art, free or for fee, on the web or boodled with software. You can create images with SAS/GRAPH or other software. This tutorial shows how to create image files with SAS/GRAPH, and how to imbed an image in a graph, but emphasis is on various ways to imbed image files, from any source, in web pages (and other output), using the SAS Output Delivery System Besides imbedding images in tables, graphs, web pages, etc., you can import images into Microsoft Word or PowerPoint, for use as is, or after adjustments there (clipping, resizing, and utber manipulation) without fancy expensive image editing tools. The tutorial compares characteristics, advantages, and disadvantages of image file types (OIF vs. JPEG), and explains how to minimize web download wait. SAS 8.2 is used |
proc step, proc print, output delivery system, proc template | 8 | |
| 29 | ThunderCell Plot Interpretation of Correlation Matrices Using the SAS System | George J. Hurley | Correlation matrices are quite useful in exploring relationships among groups of variables. AHhough generation of a correlation matrix is quite simple using SASe software, the Interpretation in the case of large matrices can be challenging. In The Americen Statistician, Vol. 56 No.4, p. 316, November 2002, Michael Friendly proposes the use of corrgrams, various graphical displays that allow these correlations to be visually interpreted. In practice, these are of particular use when the number of exploratory variables is large. This idea of the corrgram has been modified into the ThunderCell plot, which is based on the same principles. In Products Research Testing, these plots can convenienUy illustrate correlations between variables of interest in a fashion that allows relationships to be quickly inferred. Furthermore, ~ is of more interest and easier to explain to non statisticians than providing an unordered or alphabetically ordered matrix of correlation values | correlation, macro definition, txt, proc corr, health insurance, proc step | 6 | |
| 30 | Tips and Techniques with PROC MEANS | Andrew H. Karp | proc step, proc means, dataset, output, class variable, character variable, numeric variable, sas base | 6 | ||
| 31 | Using Different Methods for Accessing Non-SAS Data to Build and Incrementally Update That Data Warehouse | Ben Cochran | Often SAS users need to access data from non SAS sources. This is especially true when constructing a SAS data warehouse from other vendors' databases. While this task is not too difficult, sometimes unforeseen challenges can arise, especially when dealing with date values. This tutorial initially takes a look at several | date variable, data warehouse, proc sql, proc step, macro variable, libname statement, dataset, macro function, create table | 6 | |
| 32 | Using Metadata for Data Driven Programming (Updated for V8 & V9) | Brian K. Varney | Creating dynamic, data driven programs is a very powerful tool. Often we can use the metadata or the project data itself to help write our programs. This paper will introduce some of the concepts related to writing SAS" programs which will generate pieces of SAS code 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) | macro variable, proc sql, proc step, call execute, dictionary tables, call symput, macro loop, macro definition | 5 | |
| 33 | Using SAS as a Definitive Tool in Stock Market Analysis | Mike D. Tangedal | The "truth" of the stock marKet is that price movement of equities is controlled by the forces of supply and demand. Since the data of supply and demand is readily available in terms of daily summaries of stock price movements and since the data is voluminous, SAS software is a fine choice as a tool to apply definitive measures to recent price hiStory. Given the price ranges and the trading volume from day to day, this simple program can derive relative strong areas of both supply and demand in relation to the current price. This summary can be acted upon in terms of whether to buy, sell, or hold | sample size, sample, transaction data | 4 | |
| 34 | Using SAS Output Delivery System to Calculate the Probability Value for the F-Test Used to Compare Variance Components | Sandra E. Weinert, Timothy L. Beck |
In the realm of medical diagnostics, there is often a desire to modify a device by offering new features. But it is important to show that the essential performance of the device has not been changed by the modifications. It is always necessary to show that the precision of the new device is not significantly worse than the precision of the old device. That is, test the hypothesis: 2 2 2 2 H 0 : (J' old = (J' new versus H a : (J' old ¢: (J' new There may also be interest in knowing if the precision has been significantly improved, thereby testing a different hypothesis. Before the release of SAS version 7, it was necessary to first calculate the variance component, and then manually enter the data to perform the F -test. With the launch of the Output Delivery System (ODS), this testing can be automated without manual entry, thereby simplifying the process and reducing the risk of errors |
output delivery system, degrees of freedom, anova, proc step | 8 | |
| 35 | Using SAS Special Missing Values to Enhance Display and Analysis of Survey Research Data | Francine Cannarozzi | missing value, proc freq, sample, proc step | 3 | ||
| 36 | Using the SAS Statistical Tool from Thesis to Career: Current Experiences and Future Outlook | Jean Chen | The class, Small Systems Computer Applications in Education, at the University of North Dakota was designed to teach graduate students in the College of Education whose background in statistics may be weak and have absolutely no familiarity with the SAS System. The 14-week 3-hour class was divided into three sections. An introductory section reviewed fundamental concepts in research methodology and statistics. The second session started out with EXCEL, ACCESS, and SPSS software for statistical analysis. The third section was on data input and statistical analysis with SAS software. All programming concepts were taught at an introductory level. This SAS session provided detailed examples of how the students should key data and write the statements that create a SAS dataset, prepare the SAS program, and interpret the results for a representative research problem |
data science, sas programming, proc step, statistical software, excel, dataset, regression analysis | 3 | |
| 37 | Web Communication Effectiveness: Design and Methods to Get the Best Out of ODS, SAS, and SAS/GRAPH | LeRoy Bessler | Web Presence is no guarantee of Web Accessibility or Web Usability. Communication effectiveness on the Web requires you to: (a) get your message found (you want those search engines to find your web pages); (b) deliver your message quickly (download time is the Number One web user concern); and assure that the receiver sees the same message that you, the sender, saw when you created it (this is NOT automatic, since unexpected things can happen with, e.g., colors and fonts). This is a presentation about best technical practices, key design ideas, and The Power of Simplicity for publishing information on the Web. Though not a main focus of the presentation, the paper includes: macros to facilitate creation, with ODS PROC TEMPLATE, of communication-effective web pages, and of an improved Table of Contents to use when publishing a collection of web pages; a macro to generate font samples (not handled by PROC GFONT); and a macro to test readability oftexl colors on background colors |
proc step, output delivery system, sample, macro loop, ods listing, proc template, macro definition, macro conditional | 10 | |
| 38 | Working with SAS Data and Time Functions | Andrew H. Karp | sysdate9, datetime variable, date variable, datepart, time variable, datetime, raw data, dataset, time, time series analysis, proc freq, input statement, numeric variable, sas programming, sas 9, subsetting if | 9 |
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