SCSUG 2007 Papers - Index

52 papers. Source: SCSUG (South-Central SAS Users Group) conference proceedings.

#	Title ×	Authors ×	Abstract ×	Keywords ×	Pages
1	%STPBEGIN: How SAS Enterprise Guide Almost Removed the "L" Word from My Relationship with SAS	Rupinder Dhillon, Peter W. Eberhardt	Somewhere in the SAS Enterprise Guide documentation we read how easy it was to create a SAS stored process - write and test your code, add a simple %stpbegin and %stpend and let SAS Enterprise Guide take care of the rest. Presto, a new stored process ready to conquer the enterprise. Although that might work in the Hello World example, our first stored process project proved that applying the same guidelines to a more complex SAS program was much more challenging. In reality, creating stored processes is more involved than adding the basic syntax, input parameters and macro variables. You must also be aware of the differences that exist between SAS Enterprise Guide and PC SAS sessions, the importance of efficient coding, and the distinctions between the Workspace and Stored Process servers. This paper will step through some "gotcha's" that may stump you when converting existing code or creating new stored processes from scratch	sas enterprise guide, macro variable, excel	7
2	A "SAS Programmer's" Guide to SAS Enterprise Guide	Rupinder Dhillon, Marje Fecht	You have been programming in SAS for a while….. You hav e been told "we are moving to Enterprise Guide" and removing Display Manager". You say …… I can program everything just fine myself, thank - you! OR What am I supposed to do with all these windows? This presentation will demonstrate how SAS programmers can use SAS Enterprise Guide as their primary interface to the SAS system while maintaining the flexibility of writing their own customized code. We will look at how to navigate the views and menus how SAS Enterprise Guide can be used as your primary SAS Editor * how you can leverage the more complex built-in capabilit ies available in SAS Enterprise Guide to further enhance the information you deliver. Enterprise Guide version 4.1 will be used	sas enterprise guide, bar chart, sas programmer, proc step, sas log, dataset, proc sql	20
3	A Hands-On Introduction to Using PROC TABULATE	Thomas J. Winn Jr.	`PROC TABULATE` is used to build tabular reports containing descriptive statistical information, including hierarchical relationships among variables. The code that is used to invoke `PROC TABULATE` is complicated, and much of it looks quite different from other SAS procedures. Nevertheless, it is well worth the necessary investment of time and effort for learning the intricacies and subtleties of its syntax. Besides providing a simplified, step-by-step approach for coding `PROC TABULATE`, the hands-on workshop that accompanies this paper also will provide some practical experiences for participants	proc tabulate, proc step, class variable, proc freq, missing value, proc means	20
4	A Quick Comparison of SQL and SAS Coding Techniques for Basic Programming Tasks	Don Boudreaux		proc sql, libname statement, proc print, proc step, sas programming	59
5	A SAS Macro for Hosmer and Lemeshow's Purposeful Selection Model Building Algorithm: Description and Performance	David Williams, Zoran Bursac, David K. Hosmer	A common problem in many model-building situations is to choose from a large set of covariates that should be included in the "best" model. An additional consideration in modeling epidemiological data is the inclusion of confounders, which adds a quirk in the modeling procedure in that statistical significance is not the main criteria for keeping predictors in a model. Hosmer and Lemeshow (2000) describe a purposeful selection of covariates algorithm within which an analyst makes a variable selection decision at each step of the modeling process with a primary goal of inclusion of important confounder terms. In this poster we introduce a macro, %PurposefulSelection, which automates this process. We conduct a simulation study to compare the performance of this algorithm with three well documented variable selection procedures in SAS `PROC LOGISTIC`, FORWARD, BACKWARD, and STEPWISE. Results and implications are discussed in this presentation	sample, proc logistic, macro variable, logistic distribution, feature selection, sample size, forward selection, proc step, logistic regression, backward selection, estimate, regression analysis, main effect	6
6	A Shared Goal, Secure Metadata	Minh Duong	SAS Metadata is a critical component of the SAS Intelligence Platform. SAS provides access to the metadata from a variety of environments. This interoperability provides access to metadata from SAS applications as well as in-house applications. This flexibility reduces the need for multiple metadata servers but also increases the need to secure your metadata. Protecting metadata from unauthorized access, use, destruction, or modification is key to any security policy. In this paper we examine authentication, authorization decisions, and securing metadata objects	access control, relational database	12
7	Adapting SQL for SAS - A few ways to Maximize Performance	Rena Manning	Why is my query taking so long to run? This paper suggests a few answers to that question and then shows ways to improve query performance by taking a journey through Oz. The techniques presented were developed using SAS against (it is a battle, after all) a DB2 database on an IBM Mainframe (z/OS). It is hoped that most of the principles are general enough in nature to be useful in other environments, with appropriate yet minor modifications	proc sql, where statement, proc step, inner join, macro variable, create table	11
8	Adventures in Arrays	Jane Stroupe	Do you need to perform repetitive calculati ons on a group of variables create many variables with the same attributes restructure your data perform a table lookup with one or more factors? If your answer is "YES" to any of these questions, you should consider using an array in your `DATA STEP`	array, do loop, dataset, lookup, numeric variable, array bounds, variable list, length statement	12
9	An Introduction to SAS Stat Studio: A Programmable Successor to SAS/INSIGHT	Rick Wicklin, Peter Rowe		histogram, data science, exploratory data analysis, logistic distribution, line chart, dataset, logistic regression	18
10	Beginning Macro Design Issues	Toby Dunn, H. Ian Whitlock	Macro!!! Why does this word strike fear into even the most battle hardened SAS programmers? The word macro conjures up visions of complex and convoluted programming which leads to hours of confusing debugging a nd mind-twisting logical problem solving. Does macro pr ogramming have to be this hard? No, it does not. With a little forethought and some careful planning, practically anyone can follow a few simple design principl es and turn a complex and seemingly confusing macro problem into a simple , easy-to-follow macro. Although this paper is not a comprehensive discussion of macro design issues, the instructions provided will give the reader a basic foundation on which to start writing clear and concise macros. While programmers of all levels can learn something from this paper, the beginner and intermediate skille d SAS programmers are the intended audience	macro variable, macro parameter, %macro parameters, in=, keyword parameter, macro call, macro loop, create table, macro definition, sas programmer, proc step, proc sql	19
11	Calling C++ Program	Richard A. DeVenezia, Judy Loren	An experienced SAS coder can tackle almost any situation. However, there are occasions when a dance, not a tackle, is in order. The CALL MODULE routine is a great dance partner. A prominent healthcare data analysis firm needed to assign Diagnostic Related Group codes (DRGs) to the claims in their data warehouse. Information and instructions on assigning DRG codes is publicly available, and the firm has SAS coders that could implement the metrics. But the most beneficial solution did not involve writing SAS code to assign the DRGs. Instead, a low-cost module (a C-callable shared object) was purchased from a third party provider in the DRG data processing marketplace. The CALL MODULE routine allowed SAS to use the methods in the object like a `DATA STEP` function. This paper will explain how to call an external module from SAS on the Linux platform, and will share the lessons learned in implementing the selected DRG grouper	character variable, decimal	10
12	Coastal Fisheries data retrieval and reporting using SAS-SQL.	Fernando Martinez-Andrade	The Texas Parks and Wildlife Department, through its Coastal Fisheries Division, collects every year thousands of fishery-independent samples to monitor trends of species found in coastal waters. Every one of these samples provides a vast array of hydrological and biological data continuously stored in a Sybase relational database. SQL statements are used to formulate queries for gathering data and perform simple mathematical operations, such as, means, catch rates, length frequencies, etc. SAS procedures are used to perform more complex mathematical operations and statistical analyses, such as, summary statistics, correlation, regression, principal component, etc. Examples of SAS-SQL programs developed by the Coastal Fisheries Division to retrieve data from the Resource Monitoring Program and output reports are presented		6
13	Convert your SAS/IntrNet Applications to SAS 9 Stored Processes	Heather Weinstein	To more fully leverage the capabilities of the SAS9 Enterprise Intelligence Platform, you can convert existing `SAS/INTRNET` applications into SAS Stored Processes. Many features are implemented in the SAS Stored Process Server and the SAS Stored Process Web application to minimize the code changes required during a conversion. Existing `SAS/INTRNET` Application Dispatcher programs can usually be converted to streaming stored processes with minimal or no modifications. This paper explains how to perform such a conversion and discusses some of the differences between Application Dispatcher programs and stored processes	catalog entry, sample, macro variable, sas management console, put statement, output delivery system, sas log, ods html, variable, sas enterprise guide	18
14	Create Flowcharts Using Annotate Facility	Priya Lakshmi Saradha, Gurubaran Veeravel	With mounting significance to the graphical pres entation of data in different forms in the pharmaceutical industry, as well as in other indu stries, the need to create non-traditional graphs (flowcharts, super-imposing different types of graphs, etc.,) has incr eased in recent times. This paper will lay a strong foundation for the creation of flowcharts with the help of the ANNOTATE facility by discussing the newly developed ma cro, FLOWAN. FLOWAN can create a highly- customized flowchart with multiple levels using ANNOTATE macros and functions. Using a dataset as input, FLOWAN can represent various populations in a study or any other type of data in the form of a flowchart. This macro uses very few parameters like, the number of tiers (levels), the number of boxes in each level, the variables to display and the link or predecessor for each of the boxes. The output from this macro will present the data in an innovative way	in=, bar chart, line chart, disposition table, adverse events	7
15	Deploying Predictive Models in the Newspaper Industry	April Wilson, Kuao-Tien Chen		regression analysis, sample, confusion matrix, proc hpsplit, feature selection, gain chart, lift	23
16	Does Anybody Know What Time (or Day) It Is?	Keith Cranford	SAS date and time functions provide flexibility to do many things. This paper will provide a comprehensive overview of how SAS dates, times and datetimes work. Many of the SAS date/time functions, formats and informats will also be presented. Many will be familiar, but some are either new to SAS9 or contain new features. Working with Dates A SAS date value is simply the number of days between January 1, 1960 and the date being stored. For example, January 1, 1960 is stored as 0 (zero), January 2 as 1, and January 1, 1961 as 366 (1960 was a leap year), etc. 01Jan1960 02Jan1960 01Jan1960 0 1 366 -365	date variable, sysdate9, input statement, datepart, today	11
17	Efficiencies of Using Count Data Rather than Raw Data in Regression	Steve Fleming	Running SAS regression procedures such as `PROC REG` and LOESS on large datasets can be quite time-consuming. However, when the data can be summarized as a smaller set of unique values coupled with a count of the number of cases having each unique value, a significant amount of time can be saved for some procedures. A motivating example involving prediction of scal e scores on the Texas Assessment of Knowledge and Skills (TAKS) using prior year scores will be presen ted. Simulated data will be used to assess how the number of records and level of data redundancy affect the time saved	cpu time, proc step, regression analysis, proc reg, raw data, sample, proc gplot, proc loess, proc sql	10
18	Ensuring You Have the Proper Resources for Your SAS 9 Applications	Tony Brown, Margaret A. Crevar	Several previous SUGI papers address performance-problem troubleshooting with SAS9 applications. This paper contains information to help you manage and monitor your computer environment to ensure that you have adequate resources to support your SAS9 applications. The paper briefly describes the infrastructure that is needed for various SAS applications (from simple SAS jobs to the most complicated SAS9 Enterprise BI applications). It then shows how to identify which system infrastructure resource areas are most under pressure; and how to continually monitor them by using simple, operating-sy stem tools and more-complex, third-party monitoring applications. The monitoring and resulting resource m anagement advice will help ensure that you can meet the demands of your SAS users	batch job, sas enterprise guide, sas batch, libname statement, proc step	5
19	Excelling with SAS	Faron Kincheloe	You want to present your data using the formatting and power of an `EXCEL` spreadsheet. However, you want to use SAS to extract and periodically update the data on which the spreadsheet is based. Using the improved functionality of the `EXPORT` procedure in SAS 9 to write to a specific sheet, you can have your format and update it, too	excel, proc export, xls, structured data	3
20	Explaining Unexpected Log Messages and Output Results from DATA Step Code	Debbie Buck, Larry Stewart	Everyone knows that you should always read the SAS log every time you execute a SAS program, especially if it includes a `DATA STEP`. When you read the log, do you ever find SAS notes or warnings that puzzle you? You know the ones like "The variable XYZ is uninitialized" or "The variable ABC in the DROP, KEEP, or RENAME has never been referenced." But when you look at your output everything seems to be okay. So what do those messages mean and should you be concerned? Do you submit DATA steps that produce no notes or error messages in the log, but the code produces unexpected results? For example, you write a basic IF/THEN statement to delete specific observations, but it deletes all the observations. If you answered yes to any of the questions above, then this might be the presentation for you. This presentation focuses on common unexpected notes in the SAS log and why they occur. It also addresses common logic errors in DATA steps that lead to unexpected results	sas log, missing value, input statement, dataset, sas output, character variable, set statement, error message, if-then-else, length statement, proc print, proc step, sysdate9, format statement, put statement, subsetting if, character functions	13
21	Exploring the World of PROC SQL Joins	Kirk Paul Lafler	Real systems rarely store all their data in one large table. To do so would require maintaining several duplicate copies of the same values and could t hreaten the integrity of the data. Instead, IT departments everywhere almost always split their data among several different tables. Because of this, a method is needed to simultaneously access two or more tables to help answer the interesting questions ab out our data. This presentation illustrates a variety of join processes including Cartesian Product joins, equijoins, many table joins, and outer joins	proc sql, where statement, inner join, data merging, proc step, right join, select	6
22	Getting Started with SAS/IntrNet - A Quick and Dirty Tutorial	Gabe Cano		dataset, ods html, sas programmer, proc sql, libname statement	15
23	How Do I Love Hash Tables? Let Me Count The Ways!	Judy Loren	I love hash tables. You will, too, after you see what they can do. This paper will start with the classic 2 table join. Nothing new, you say? But this version does it in one step without sorting. And, it's the fastest method around. Next, you will see the use of hash tables to join multiple datasets on different keys in one pass, again with no sorting. How about unlimited recursive chained lookups (like when you need to update an ID through as many incarnations as it may have had)? Hash tables solve that one, too. And before you catch your breath, you'll see how to create n datasets from one (or more), where n is determined (at runtime) by the number of values encountered in a variable. No muss, no fuss. One step (well, OK, this one does require a prior sort) and you're done. We'll wind up with an outer join, just to show that hash tables can do that, too. Take a look at what they can deliver, and you'll be counting the ways you love hash tables before the year is out	hash table, conditional do loop, hash iterator, pdv, do loop, dataset, out=, proc means, key	14
24	How to Excel with SAS	Keith Cranford		excel, proc step, dataset, libname statement, proc import, proc export, name range list, proc print	12
25	How to Import a Text File with a Large Number of Variables But The Layout Stored in a Separate File?	Mu Hu, Steven Yan	`PROC IMPORT`, Import wizard, and the `DATA STEP` are useful tools to convert text files into SASi data sets. However, when it comes to read a text file with a large number of variables but the layout detailed in a separate file, all these tools have limitations. The `PROC IMPORT` and the Import Wizard won't be able to read the variable names because they were stored in a separate file; while the `DATA STEP` has better control in this aspect, it is hard for SAS programmers to hard code and to update hundreds even thousands of variables, which oftentimes resulted in human errors. This paper presents a method that will effectively handle this challenge	txt, proc step, proc import, data step, proc sql, sas programmer, sample	5
26	How to Incorporate Old SAS Data into a New DATA Step, or "What is S-M-U?"	Andrew T. Kuligowski	S-M-U. Some people will see these three letters and immediately think of the abbreviation for a private university and associated football team in Texas. Others might treat them as a three-letter word, and recall a whimsical cartoon character created by Al Capp many years ago. However, in the world of the SAS user, these three letters represent the building blocks for processing SAS datasets through the SAS `DATA STEP`. S, M, and U are first letters in the wo rds SET, MERGE, and UPDATE - the 3 commands used to introduce SAS data into a `DATA STEP`. This presentation will discuss the syntax for the SET, MERGE, and UPDATE commands. It will compare and contrast these 3 commands. Finally, it will provide appropriate uses for each command, along with basic examples that will illustrate the main points of the presentation. `SET` Statement According to the Version 6 SAS Language	dataset, libname statement, set statement	9
27	Individual Growth Analysis Using PROC MIXED	Maribeth H. Johnson	Individual growth models are designed for exploring longitudinal data on individuals over time. `PROC MIXED` allows the growth parameters for each individual to be examined as random effects in the model. Individual-level covariates can be entered into the model as fixed effects to determine their impact on the dependent variable alone and in interaction with the growth parameters. The structure of the variance-covariance matrix of the repeated measurements can also be examined and entered into the model. A model building exercise will be demonstrated using up to eight systolic blood pressure measurements of youths aged 7-22	proc mixed, correlation, covariance, fixed effects, group by, covariance structure, estimate, longitudinal data, proc step, likelihood function, proc freq	10
28	List Processing Basics: Creating and Using Lists of Macro Variables	Ronald J. Fehd, Arthur L. Carpenter		macro put, macro variable, proc sql, proc step, call execute, macro call, macro loop, macro definition, %if-%then-%else, output delivery system, do loop, proc report, dictionary tables, data step, create table, proc sort, macro function	21
29	Market Research using SAS, Ruby-on-Rails, and Sawtooth	Tom Taylor	Market research over the web seems common, but most commercial surveys require robust systems that can be custom designed for the nuances of the specific customer. Do-it-yourself survey websites such as Zoomerang are not adequate. The client wants complete control that only a custom survey site can offer. These commercial surveys are for product design optimization, quality of service, and client satisfaction. Over the past year, the author has created and executed several customer surveys with surprising efficiency. He has found Ruby-on-Rails to be an ideal development environment for the web interface. Back-end analysis is still best done with SAS and sometimes `EXCEL` pivot tables. For product optimization studies, the conjoint model from Sawtooth Software has proved to be very cost effective. Some of these studies have been done in four languages simultaneously. Hosting has moved from rented web-farm servers to geographically separated Mac-Mini's	web service, regression analysis	7
30	More Tricks and Tips for SAS/Internet	Dan Hammarstrom, Keith Cranford	Have you wanted to include tabs in your `SAS/INTRNET` applications? Would you like an easier way to construct dynamic HTML forms? Have you wanted more control of your inline help? Taken from real world experiences, these techniques, as well as others, will be presented to help speed up your `SAS/INTRNET` application development. The paper includes SAS code, Javascript and Cascading Style Sheets	proc step, proc report, excel, ods html, proc sql, title statement, dataset, macro variable	27
31	PROC REPORT: Doin' It in STYLE!	Ray Pass, Sandy McNeill	The advent of the SAS Output Deliver y System (`ODS` to its friends) has turn ed SAS reports from machine-generated, black & white monospace bores into people-pr oduced, productive and reader-friendly information displays. One of the m ain principles underlying `ODS` is the use of Table and Sty le d efinitions (also known as Table and Sty le templates). Most procedures hav e a standard output la yout structure and rely on their Table and S tyle definitions to gov ern the cosmetic or stylistic appearance of th eir tables. Cert ain procedures (REPORT, TABULATE, etc), however, by the very nature of their complete structural customizability, do not rely on fixed external table definitions. For these procedures, stylistic customizations are performed through the use of the STYLE option, an `ODS` concept which is integrated into the heart of the procedures' syntax. This presentation will demonstrate the use of STYLEs in the `REPORT` procedure	proc report, proc step, ods html, cpu time, user-defined format	15
32	PROC SQL for New Users	Kirk Paul Lafler	Structured Query Language (`PROC SQL`) is a database language found in the base -SAS software. It enables access to data stored in SAS data sets or tables using a powerful assortment of statements, clauses, options, functions, and other language features. This hands -on workshop presents core concepts of this powerful language as well as its many applications, and is intended for SAS users who desire an overview of the capa bilities of this exciting procedure. Attendees will explore the construction of simple SQL queries, ordering and grouping data, the application of case logic for data reclassification, the creation and use of views, and the construction of simple inner and outer joins	proc sql, where statement, proc step, select, inner join, index, order by, view, data merging, right join	13
33	PROC TABULATE: Doin' It in STYLE!	Ray Pass, Sandy McNeill	The advent of the SAS Output Delivery System (`ODS` to its friends) has turned SAS reports from machine-generated, black & white monospace bores into people-produced, productive and r eader-friendly information displays. One of the main principles underlying `ODS` is the use of Table and Style definitions (also known as Table and Style templates). Most procedures have a standard output layout structure and rely on their Table and Style definitions to govern the cosmetic or stylistic appearance of their tables. Ce rtain procedures (REPORT, TABULATE, etc), however, by the very nature of their complete structural customizability, do not rely on fixed exte rnal table definitions. For these procedures, stylistic customizations are performed through the use of the STYLE option, an `ODS` concept which is integrated into the heart of the procedures' syntax. This presentation will demonstrate the use of STYLEs in the `TABULATE` procedure	proc tabulate, proc step, class variable, output delivery system, ods html, user-defined format	17
34	Propensity Scoring Tutorial by Simulation in SAS	Dee H. Wu, David M. Thompson, David Bard	In certain clinical trials or observational studies, proper random assignment of treatment and control groups is not always possible, so that selection bias may become an issue. Recent efforts to address issues of nonrandom assignment, including a class of methods known as 'Propensity Scoring,' are alternatives to reduce bias in the estimation of treatment effects when assignment is not random. The original technique was described by Rosenbaum and Rubin in 1983. However, we have found that much of current literature describes the technique using a large number of mathematical constructs. The multiplicity of mathematical approaches reduces the techniques' accessibility to users from different interdisciplinary departments. Failure to understand the statistical method deters proper usage. We will first describe the technique through diagram and simulation to improve teaching and understanding the material intuitively in SAS	propensity score, treatment effect, regression analysis	11
35	Quality: Baylor Health Care System	Neil S. Fleming			47
36	SAS Applications in Support of Off-the-shelf, Affordable, WiFi-Controlled Robots	Cecil R. Hallum, Huixing He, Jason Minter	The application of clustering and discriminant analyses to digitized imagery can enhance multivariate strategies that inco rporate in spatial information and improve classification accuracies of pixels into distinct classes. This paper reports on a SAS implemented, initial approach that investigates vector augmentation , real-time search strategies, opti mal clustering, and a proposed "detection" approach to seek out and find sought-a fter objects across numerous digital photos. The majority of the technica l details, documented in the first and second authors' M.S. theses (Minter (2006) and Huixing (2007)), are ex cluded because of the required brevity of this report	mahalanobis distance, proc princomp	12
37	SAS Formats - Simply Powerful	Howard Hagemann		proc format, proc step, format statement, informat statement, numeric variable, attrib statement, proc freq, missing value, put statement, input statement	12
38	SAS Macro Programming Tips and Techniques	Kirk Paul Lafler	The SAS Macro Language is a powerful tool for extending the capabilities of the SAS System. This hands -on workshop presents numerous tips and tricks related to the construction of effective macros through the demonstration of a collection of proven Macro Language coding techniques. Attendees learn how to process statements containing macros; replace text strings with macro variables; generate SAS cod e using macros; manipulate macro variable values with macro functions; handle global and local variables; construct arithmetic and logical expressions; interface the macro language with the `DATA STEP` and `SQL` procedure; store and reuse macros; troubleshoot and debug macros; and develop efficient and portable macro language code	macro facility, proc step, autocall macro, macro definition, macro variable, macro function, macro parameter, %macro parameters, proc sql, dictionary tables, options statement	8
39	SAS Web Report Studio - Enabling Flexible Reporting for End-Users	Kevin Davidson	SAS Web Report Studio is a web reporting tool that allows end-users to develop, run, and share reports utilizing an intuitive interface. As the name implies, end-users only need a web browser to develop and run the reports. This paper will discuss features, limitations, server requirements, security options, and provide some practical how-to tips	excel, sas management console	6
40	Setting Up PC/SAS for Batch Processing	Ronald J. Fehd	This paper presents an overview of issues of usage of PC-SAS R⃝ in a project directory . T opics covered include directory structure, how to start SAS in a particular (project) directory , SAS command line in- vocation, location and modification of SAS config- uration files, creation and usage of a project au- toexec.sas, and directing output in various formats, - e.g.: html, rtf, or xls - to appropriate directo- ries. Example programs are executed with Windows batch files so that each program's log and list can be examined separately . Issues of program reuse, i.e., either as macros or include files, are addressed in the discussion of an autoexec. This is not an introduction to SAS programming course but it is about how to manage SAS program- ming. Expected audience is all users of PC-SAS, espe- cially anyone using SAS for more than one project. Keywords: PC-SAS Windows. Contents	proc step, sas library	9
41	So You're Still Not Using PROC REPORT. Why Not?	Ray Pass, Daphne E. Ewing	Everyone who can spell SAS knows how t o use `PROC PRINT`. Its primary use may be as a devel opment tool to help in debugging a long multi-step program, or as a simple report generator when all that is really needed is a quick look at the data, or even a basi c l ow-level fi nished report . However, i f a report generat ion/information del ivery t ool wi th powerful formatting, sum marizing and analysis feat ures is called fo r, th en `PROC REPORT` is th e so lution. `PROC REPORT` can provide the standard `PROC PRINT` fu nctionality, b ut in ad dition, can easily p erform m any o f th e task s th at yo u wo uld otherwise have to use the SORT, MEANS, FREQ and TABULATE procedures to accom plish. `PROC REPORT` is part of the Base SAS product, can run in both an interactive screen-painting mode or a bat ch mode, and should be the basic tool of choice when there is a need to produce powerful and productive reports from SAS data sets	proc report, proc step, class variable, character variable, proc print, proc means, proc tabulate	13
42	Some SAS techniques used in Health Care Analysis	Wei Yu		proc sql, create table, proc step	4
43	The Impact of Data Visualization in a Study of Chronic Disease	Gabe Cano, Brad Smith, Paul Cuddihy		proc means, data visualization, missing value, dataset, clinical trial, raw data, sample	17
44	The Output Delivery System (ODS) from Scratch	Kevin D. Smith	The Output Delivery System (`ODS`) is a great way to move beyond reports that just use the listing output. Using `ODS`, you can generate reports in formats such as HTML, XML, PDF, PostScript, RTF, and Microsoft `EXCEL`. This paper tells you what you need to know to generate reports with `ODS`, from scratch. You'll learn how to generate multiple output formats, simultaneously; how to change the look of your report using styles; how to add text passages; and other "neat" tips (that is, helpful information)	proc step, output delivery system, proc template, proc contents, excel, sas output, sample, ods html, select, ods listing	14
45	The Power of the BY Statement	Toby Dunn, Paul A. Choate		by group processing, proc step, group by, proc sql, data step, output, update statement, merge statement, set statement, conditional do loop	11
46	Thinking in Sets	Joe Celko		proc sql, group by, proc means, create table, update statement, where statement, central tendency	60
47	Undocumented and Hard-to-find Features in PROC SQL	Kirk Paul Lafler	The `SQL` Procedure contains many powerful and elegant language features for SQL users. This paper presents SQL topics that will help users unlo ck the many hidden features, options, and other hard -to-find gems found in the SQL universe. Topics include CASE logic; the COALESCE function; SQL statement options _METHOD, _TREE, and other useful options; dictionary tables; the `PROC SQL` - macro interface; and performance tuning strategies	proc sql, proc step, macro variable, sas library, missing value, macro definition	10
48	User-Written DATA Step Functions	Jason Secosky	For years, users have asked for the ability to write functions in `DATA STEP` syntax. The day has come when this is possible. In SAS9, the `FCMP` procedure provides the ability to write functions using `DATA STEP` syntax. In SAS 9.2, these functions can be called from a `DATA STEP`. This paper explains how to write functions with `PROC FCMP` and how these functions are invoked from a `DATA STEP`. It also contains caveats when calling `PROC FCMP` functions from a `DATA STEP`	put statement, return, proc step, proc fcmp, file statement	9
49	Using INFILE and INPUT Statements to Introduce External Data into the SAS System	Andrew T. Kuligowski	The SAS System has numerous capabilities to store, analyze , report, and present data. However, those features are useless unless that data is stored in, or can be accessed by, the SAS System. This presentation is designed to review the INFILE and I NPUT statements. It has been set up as a series of examples, each building on the other, rather than a mere recitation of the options as documented in th e manual. These examples will include various data s ources, including `DATALINES`, sequential files, and `CSV` files. GETTING STARTED - BASIC INFILE / INPUT with DATALIN ES In order to bring data from an external source into your SAS session, the user must provide the answer s to a couple of simple questions: Where is the data, and what does it look like? The INFILE statement will define the data source and provide a few tidbits of information regarding its form, while the INPUT statement will define the format of the data to be processed	input statement, infile statement, excel, pointer control, proc print, proc step, length statement, filename statement, list input, variable, character variable, missing value, proc format, run, out=	18
50	Using Links, Arrays, and Do-Loops	Jimmy A. DeFoor		conditional do loop, dataset, do loop, do over, point= option, return, output, character variable, random sampling, array, array bounds, raw data, proc step	13
51	Using SAS SYSPARM and other automatic variables	Clarence W. Jackson	This paper primarily reviews the BASE SAS SYSPARM automatic variable, what it is, how it is used, and provides examples for using it to conditionally execute SAS code. Use of SYSPARM can prove very useful in producti on type SAS jobs that must have the same conditional information updated with each ex ecution by reducing the updates to the source code. SYSPARM can be updated befo re execution, accessed in a SAS program, and also be updated in the SAS program. In addition, this paper briefly reviews other selected automatic variables that are created at SAS session invocation. These are SYSJOBID, SYSUSERID, `SYSDAY`, `SYSDATE`, SYSDATE9, SYSTIME, SYSSCPL, SYSVER, and SYSVLONG. Unlike SYSPARM, these are read only variables	macro variable, automatic variable, macro parameter, options statement, filtering	8
52	What Can DQ Do for You?	Faron Kincheloe	The SAS Data Quality Server module brings the power of DataFlux into the SAS platform. This can be extremely beneficial for those who are already using SAS to manipulate and cleanse data. Baylor University is using this functionality to identify duplicates in its contact database and standardize organization names. This paper provides an overview of SAS Data Quality Server and how Baylor University is using it to save money and improve its customer relations	adam dataset, proc sql, excel	11

Back to Conf go 2008 go 2006

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.