SESUG 1999 Papers - Index

83 papers. Source: SESUG (SouthEast SAS Users Group) conference proceedings.

#	Title ×	Authors ×	Abstract ×	Keywords ×	Extras	Pages
1	14 Steps to a Good GUI	John E. Bentley	Creating a graphical user interface is clearly very different from writing program code, but with `SAS/AFÂ` , FRAME Entries, and Screen Control Language the user interface and program code can be almost indistinguishable. This makes SAS application development easier and faster. Programmers, unfortunately, usually do not have visual design training so too often the result is a clumsy interface running powerful code. Luckily, there are straight-forward methodologies for GUI design that can be easily implemented. Drawing primarily on the work of consultant and author Susan Fowler, this paper will present an overview of a 14- step methodology for designing a good GUI. No experience with application development is required although it would be helpful	excel, audit trail	source	6
2	A Cross-reference for SAS Data Libraries	John R. Gerlach, Cindy Garra	SAS data libraries often resemble a relational model when the several data sets contain common variables, or in the vernacular of relational theory, common attributes exist across two or more tables. In order to develop an understanding of a SAS data library, it is useful to recognize these common variables, especially those that define observations, in an attempt to perceive a relational model. Using Dictionary tables in SAS, it's possible to produce a cross-reference of all the variables and data sets (i.e., attributes and tables) that exist in a data library. The cross-reference offers immediate insight about the data library, its organization and relationships. This paper discusses Dictionary tables and explains a macro that produces a cross-reference report on any SAS data library	libname statement, proc sql, dictionary tables, macro variable, create table, order by, macro loop, macro definition, proc report, proc step, %if-%then-%else	source	5
3	A Modular SAS Programming to Support ABCTM Simulation Study	Sejong Bae	A huge program composed of one long line can be divided into a number of sub-programs. A modular programming technique has been adapted to study the properties of ABC TM under various simulated conditions. A modular programming technique has several advantages over one large program. It provides easier coding, debugging, and plug-in use to various situations, ABC TM is a tool to facilitate the measurement, comparison and dissemination of high levels of performance derived from the process of care practices already being achieved by "best-in- class" providers		source	3
4	A Modular SAS Programming to Support ABCTM Simulation Study	Sejong Bae	A huge program composed of one long line can be divided into a number of sub-programs. A modular programming technique has been adapted to study the properties of ABC TM under various simulated conditions. A modular programming technique has several advantages over one large program. It provides easier coding, debugging, and plug-in use to various situations, ABC TM is a tool to facilitate the measurement, comparison and dissemination of high levels of performance derived from the process of care practices already being achieved by "best-in- class" providers		source	3
5	A SAS Program for the Computation of Cumulative Exposure Estimates for Analysis of Cause-specific Mortality Rates in a Cohort of Synthetic Rubber Workers	Ilene K. Brill, Maurizio Macaluso, Robert S. Matthews, Elizabeth Delzell	The purpose of this SAS macro in a Windows environment is to generate SAS data sets containing person-year and numerator data for use in stratified and regression analyses of mortality rates and ratios. The data layout consists of aggregate person-year and death counts cross-classified according to categories of fixed and time-dependent variables, and of cumulative exposure to butadiene, styrene, and benzene. The program was employed to evaluate the association of chemical exposure and specific causes of death among workers employed in the manufacture of synthetic rubber. Two files containing cumulative exposure indices are created, a decedent file containing one observation for each decedent and a person-year file which contains one observation for each person year of follow-up. Relatively straightforward extensions of this program allow the dynamic allocation of person-years according to lagged exposure variables	calendar year, regression analysis	source	5
6	A SAS Program to Calculate and Plot Widths of (1-α)100% Confidence Intervals for Binomial Proportions	Maribeth H. Johnson, Mark S. Litaker	The width of a confidence interval around the estimated proportion may be used as a measure of the precision of a measurement obtained in a study with a given sample size. A SAS /c26 program is presented which calculates the (1- )100% confidence intervals of binomial proportions, using the F-distribution, for a range of sample sizes and proportions. Plots of confidence interval widths across the expected range of proportions which may be observed are an aid in determining the sample size necessary to achieve a desired level of study precision	confidence interval, sample, sample size, binomial distribution	source	2
7	A SAS7 SYSTEM: FROM CD TO GIS MAPS	Samuel D. Calhoun	Once a year the Rural Business and Development Policy Branch, Economic Research Service, USDA, publishes an issue of Rural Condition and Trends (RCaT), dealing with Federal Programs. This issue describes Federal program and policy changes affecting rural America. The original data comes from the Bureau of the Census in CD- ROM format. The data is in ASCII format. It consist of over 350,000 records. A transformation process of the data takes place before the RCaT is produced. The majority of this process uses base PC-SAS version 6.12 for Windows Next Technology (WINNT) and some mainframe SAS programs. In addition to the SAS programs there are some FORTRAN 7 programs. The purpose of this paper is to show how SAS plays a major role in manipulating the data in order to produce maps (see figures 1 and 2) for a report	dataset, proc step	source	6
8	Adventures in Arrays: A Beginning Tutorial	Jane Stroupe	Do you need to perform repetitive calculations 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, lookup, variable list	source	6
9	An Interactive GUI Front-End for a Credit Scoring Modeling System	Jeffrey Morrison, Futian Shi, Timothy Lee	The need for statistical modeling has been on the rise in recent years. Banks, retailers, and even telecommunication companies are looking for better ways to reduce risks from new and existing customers. Software technology like SAS AF/FRAMES has stepped up to help meet this demand through GUI front end development, reducing programming errors and learning curves for new employees. Consulting companies providing modeling services will be most successful if they can efficiently integrate these technologies with their model building processes	response variable, regression analysis, sample	source	6
10	An Introduction to the Next Big Thing: Parallel Computing	John E. Bentley	MPP, SMP, clustered SMP, NUMA, data parallelism, shared- nothing and shared-everything architectures. Can you explain these buzzwords? You should be able to, because there's a paradigm shift coming. It is proven technology today to combine dozens or hundreds of CPUs together to build a supercomputer, and many companies are using them to host Decision Support Systems that exploit multi-terabyte data warehouses. However, largely because SAS â Software exists in the "sequential" world (with the exception of SPDSâ ), most users have never had to become familiar with parallel computing. Things are changing fast, though. Third- party software has recently become available to allow parts of SAS to execute in parallel, and the SAS Institute is working diligently on developing its own native parallel capability. This paper presents an overview of parallel computing concepts, terminology, and architectures with a goal of providing SAS users with a working familiarity of the subject	parallel processing, proc sql, data warehouse, proc step, relational database, data mining, proc sort, key, proc means, sql pass-through	source	10
11	An OBS Limit with a WHERE Condition	H. Ian Whitlock	In SAS software the OBS option is incompatible with the WHERE condition. This was a design decision instead of an inherent incompatibility: in other words, a mistake. There are several possible interpretations of how to implement both of these restrictions. A utility macro, LIMIT, is introduced to help implement a workaround for the interpretation given above. Use of the macro is first illustrated with a `PROC PRINT` and then in a macro TPRINT providing a more transparent form of solution for this important case. SAS Version 7 is assumed, since it provides a simple solution to a naming problem, but the code can be easily modified to work in 6.12 at the expense of a little more user effort. In addition to providing a useful extension to SAS, this example can be used as a learning tool for SAS macro in general and for the design of utility macros as a special case	proc step, proc print, if-then-else, %if-%then-%else, macro definition	source	2
12	Analysis of Longitudinal Data: Comparison between PROC GLM and PROC MIXED	Maribeth H. Johnson	Longitudinal data refers to datasets with multiple measurements of a response variable on the same experimental unit made over a period of time. These types of data require special attention because they involve correlated data. The relationships between repeated measurements are important in assessing reliability and tracking of those measurements. The proper variance- covariance structure in the analysis model is essential to the understanding and interpretation of those relationships. The assumption of compound symmetry necessary for correctly using the intraclass correlation as a measure of tracking can be tested against other variance structures using `PROC MIXED`. This paper compares the variance, covariance and correlation estimates obtained from the GLM and MIXED procedures of `SAS/STAT` on two sets of data, one of which has missing data	correlation, covariance, proc genmod, covariance structure, proc step, proc mixed, likelihood function, missing value, proc glm, compound symmetry, estimate, repeated measures, univariate analysis, anova	source	6
13	Array Lookup Techniques: from Key-Indexing to Hashing (Part 2)	Paul M. Dorfman			source	11
14	Array Lookup Techniques: from Sequential Search to Key-Indexing (Part 1)	Paul M. Dorfman			source	11
15	Building a Customized Data Entry System With SAS/Intrnet	Keith J. Brown		put statement, dataset, macro variable, macro facility	source	9
16	Building a Data Mart on top of SAP R/3-HR	Christ D'haeveloose, Sophie De Baets		data mart, data dictionary	source	6
17	Building Yield Management - GUI System at Norwegian Cruise Line by Using SAS/EIS and SAS/AF	Sam Sheng		data mining	source	4
18	Characteristics of a "Successful" Application	Caroline C. Bahler	An application can be judged "successful" by two different sets of criteria. The first set of criteria belongs to the users - does the application perform as required. The second set of criteria belongs to Information Systems (IS) - was the application developed on time, within budget, and is it easy to maintain and support. A truly "successful" application needs to meet both sets of criteria. Applications that meet this goal have these characteristics in common: agreed upon requirements, good documentation, parameter driven code, reusable and self-generating code, programming efficiencies when possible, and testing. The object of this paper is to discuss these characteristics and how they contribute to a "successful" application. Let Us Start at the Very Beginning… Once upon at time a Marketing Manager (MM) for the Enormous Toy Company wandered into the IS department	memory usage, proc step, proc sql	source	5
19	Comparison of CGI and Java Technology Provided in SAS/IntrNet Software	Barbara Walters	Which technology to use? The components of `SAS/INTRNET` software utilize a variety of client/server architectures. There are data servers and compute servers, CGI (Common Gateway Interface) programs, Java applets, Java servlets and enterprise Java technologies. Together, these components provide the technology for delivering sophisticated applications through a Web browser. Deciding which components are best for your application depends upon a variety of factors, including security, user interface issues, your skill set, and Internet versus intranet delivery. We will explore each of these factors and explain how to choose the best components for your application. Emerging enterprise Java technologies such as Java servlets, Enterprise JavaBeans and JavaServer Pages are not covered in this paper, but they will be discussed in the presentation associated with this paper. Note: SAS Institute continues to provide new components that exploit Web technology		source	6
20	Creating ASCII Fixed Length Record Files from SAS Data Sets	Lawrence W. Altmayer			source	2
21	CRM 101: Maximizing Return on Investment with the SAS Solution for CRM	Drury Jenkins	During the last decade, the deployment of Information Technology (IT) has been rapidly evolving from a necessary evil to a legitimate business strategy. In the early to mid 1990's Business Process Reengineering (BPR) was the hot business tool that allowed IT deployment to generate a positive return on investment (ROI) and obtain business	data mining, customer retention	source	5
22	Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing	C. Olivia Parr Rud	Data Mining is a new term for the common practice of searching through data to find patterns, which w ill predict future outcomes or define measurable relationships. Statistical and machine learning methods are the favored tools of many businesses that utilize direct marketing. This paper w ill explore some of the typical uses of Data Mining in direct marketing with discussions and examples of measuring response, risk and lifetime customer value. The paper w ill conclude with highlights of SAS Enterprise Miner and its ab ility to transform the Data Mining process	sample, logistic distribution, logistic regression, missing value, univariate analysis, regression analysis, data cleaning, interval variable, predictor variable, response variable, product profitability, standard deviation, proc step, gain chart	source	7
23	Data Summarization Methods in Base SAS Procedures	Lynne Bresler	Various base SAS procedures compute an array of statistics to summarize your data. The types of statistical reports these procedures generate differ. With Version 8 enhancements, `PROC UNIVARIATE` now produces high-resolution displays of histograms, comparative histograms, probability plots, and quantile-quantile plots, along with an optional table of descriptive statistics. The histograms can also include overlays of fitted density curves or kernel density estimates to examine the underlying data distribution. This paper compares how `PROC MEANS`, `PROC TABULATE`, and `PROC UNIVARIATE` generate descriptive statistics and describes how to use graphical displays to summarize your data	proc step, proc univariate, proc tabulate, histogram, ods html, proc means, sas base, data visualization, class variable, standard deviation, qq plot, output delivery system, proc freq	source	9
24	Distributing SAS/AF Models with Java Clients	Chris Bailey	Given the growing acceptance of the Internet and Intranet as enterprise application mediums and the need for client-server computing using open solutions, SAS Institute has recognized the need to leverage existing `SAS/AF` functionality to Java clients. This paper attempts to explain how technologies developed by SAS Institute allow clients written in Java to exploit the data and compute power of the SAS system by accessing `SAS/AF` models seamlessly in a networked computing environment. We will discuss webAF, which consists of an Integrated Development Environment and Java class libraries, that creates applications written in Java, and also how to expose new or existing `SAS/AF` models to Java using the Remote Object Class Factory	bar chart, dataset	source	7
25	Do We Know How to Function?	Janet E. Stuelpner	How do we function in SAS â ? There are many functions that can make programming easy and efficient. This paper will take a small section of the functions that are provided and explore their uses, benefits and pitfalls. There are examples of regular code as compared to a more efficient use with functions. There are also instances where a function may not be the best choice. These will be discussed as well	proc step, date variable, numeric functions, sysdate9, character variable, missing value, put statement, interest rate, time, sample, variable list, proc means	source	7
26	Effective strategies for managing SAS applications development	Christopher A. Roper	The SAS System is a powerful tool for developing applications and systems to solve the demanding information needs of the business world. As a result, SAS applications can, and frequently do, become very large and complex. As the size and complexity of these applications grow, it becomes increasingly apparent that good application development management techniques are critical to the successful implementation of the application or system. The sooner these techniques are applied the easier the task of managing the development and maintenance becomes, and the better the application can meet the demands of the information consumer. This paper will introduce some applications development management techniques that will simplify the development and maintenance of any SAS application. General techniques for setting up development, testing, and production environments will be discussed. As will the	data validation rules, macro variable	source	7
27	Empowering Your End-Users Reporting Potential from SAS/AF Applications with SAS Enterprise Reporter	Gary L. Mason	Empower the end-user, by making SAS Institute's, Enterprise Reporter (ER), a reporting tool option in your `SAS/AF` application. This gives the user the opportunity to produce presentation quality reports. For ease of access to SAS ER in your `SAS/AF` application, add it as an additional toolbar icon. This paper will illustrate that as the icon invokes ER, the layout allows the user to create an ad-hoc report. The `SAS/AF` application passes the SAS dataset into the ER Design View which allows the end-user to immediately begin producing their own high quality reports	dataset, proc report, proc step, bar chart, sas library, proc print	source	4
28	EVERYTHING IN ONE RECORD: CREATING ONE-LINERS WITH MERGES AND RETAINS	Sharon W. Stroud	In our hospital claims relational Oracle database, a patient with multiple diagnoses for one hospital stay appears in the dataset multiple times, each diagnosis distinguished by a sequence field. When analyzing this data it is best to have one record per patient stay, with all diagnosis codes in that record. The genius program coverts a 'long' dataset with multiple related records into a shorter, wider dataset using a series of merges. The new dataset has fewer records and more variables, making analysis much easier. The genius2 program performs the same conversion more efficiently, making use of the retain statement	retain, missing value	source	3
29	Exporting Oracle Tables into SAS Tables Made Simple with Version 7 of The SAS System	Danny Walker	Over the past few years Delta Air Lines has been involved in a major upgrade of their information system technologies. Delta Technology was created as a wholly owned subsidiary of Delta Air Lines to facilitate this process. Part of this effort was moving legacy mainframe systems to alternate platforms such as UNIX. Some were re- written as others were replaced with third party software. Tools and architecture were also standardized which include the use of relational database systems such as Oracle. As these new systems become operational, the analytical community at Delta continues to require quick and seamless access to their data. This paper demonstrates how to easily extract Oracle data into SAS tables using only Base SAS, Oracle SQL/Plus, and SQL/NET on HP V class 2250 UX11.0 connecting to Oracle 7.3.4	proc sql, data step, macro variable, dataset, macro definition	source	5
30	Forecasting Army Officer Attrition with Logistic Regression Using The SAS System	Douglas L. McAllaster	This paper explains how Army personnel analysts model and forecast officer attrition with logistic regression using SAS System software. This statistical application applies a simple logistic regression model (only one predictor variable, fiscal year) to predict a binary response, whether officers stay or leave the Army. However, the complete application is large and complex since we run this logistic regression against more than one-hundred and fifty homogeneous BY-groups (officer cohorts). Furthermore, the application is enhanced with a semi-automatic capability to identify and exclude inappropriate outliers through the usage of SAS Macro Language. Thus, this application demonstrates the power SAS Software brings (1) to summarize vast amounts of data (fourteen years of legacy data - over a million observations), (2) to model binomial outcomes and forecast trends using logistic regression, and (3) to repeat the statistical analysis code using macro language	logistic regression, regression analysis, outlier, logistic distribution, proc step, proc genmod, macro facility, predictor variable, macro definition, by group processing, proc reg, binomial distribution, missing value, response variable	source	10
31	FUZZY MERGES: Examples and Techniques	Malachy J. Foley	Frequently SASâ programmers must merge files where the values of the key variables are only approximately the same. Merging on names with approximately the same spelling, or merging on times that are within three minutes of each other are examples of these kinds of merges. These merges are often called fuzzy merges. This tutorial examines the realm of fuzzy merges. It looks at relevant techniques and gives examples of actual programs that produce fuzzy merges	retain, missing value	source	10
32	Generating SAS Reports and the Collation Problem	Imelda C. Go	Default SAS output may produce reports that are not in a desired order. For example, let X and Y be two groups. `PROC PRINT` and `PROC FREQ` that use BY-group processing (for X and Y) will produce the following output sequence: `PROC PRINT` for X, `PROC PRINT` for Y, `PROC FREQ` for X, and `PROC FREQ` for Y. The desired output sequence is output from `PROC PRINT` for X, `PROC FREQ` for X, `PROC PRINT` for Y, and `PROC FREQ` for Y. Rearranging the output manually can achieve the desired order, but why waste precious time? This paper exemplifies a number of programming approaches to the collation problem. Using SAS macros to solve this problem can be advantageous. Macros generalize repetitive routines and can reduce the number of statements needed	proc step, proc print, proc freq, macro definition, by group processing	source	3
33	Getting Started With Frame Technology	Christopher A. Roper		dataset, bar chart	source	5
34	Getting Started with Macro	H. Ian Whitlock	The macro language is a powerful tool, but it can be dangerous in the hands of the naive. This tutorial takes the first steps in building a strong foundation to understanding of the SAS /GD2 macro facility. Macro variables are introduced as parameters to a SAS program. Then `%INCLUDE` is added, and the power of this combination demonstrated. Macros are introduced as a better means of packaging code, and the consequences are explored with examples. Design issues and understanding are emphasized. The consequences of adding the `DATA STEP` functions CALL SYMPUT and CALL EXECUTE to the programmer's repertoire are considered. As an extension, very simple `PROC SQL` code is introduced to make macro variables holding lists. The power of this new tool is demonstrated with examples. If you restrict the use of macro to the above tools you have a dramatically more powerful language than SAS alone provides, and debugging is no harder than without these tools	macro variable, macro facility	source	10
35	Hiring the Best SAS Programmers	Neil H. Howard	You are interviewing a candidate in a sharp navy suit, with an impressive resume and ten years of SAS experience. But, how do you tell if this ten years of experience is really ten years, or the same year over and over again? If, indeed, past behavior or past job performance is the best indicator of future performance, how is the SAS community probing for the facts? What are our assessment criteria? The author developed a survey tool administered to selected SAS programmers, analysts, trainers, human resource experts, and managers as a reality check into our performance as interviewers. What techniques are being used to interview and assess SAS talent? This paper w ill explore the results of this survey, looking at the following interview techniques: identifying resume red flags, conducting useful phone interviews, structuring general face-to- face interviews, "measuring" intangibles, proficiency testing, and code walk-throughs	proc step, macro variable, missing value, dataset, proc freq, merge statement, sas log, sas programmer, data cleaning, proc means, macro definition	source	10
36	Hot-Deck Imputation: A Simple DATA Step Approach	Lawrence W. Altmayer	Hot-deck imputation is a means of imputing data, using the data from other observations in the sample at hand. This paper deals with a method of imputation we used for the Survey of Adults on Probation. In this method, we first attempt to impute race based on other variables in an observation. We impute the remaining missing race data, and age and gender, using the same variable in prior or latter observations in the data set. This method uses macro variables to subset the data into groups within which imputation is done. It also uses arrays to keep track of values to use for imputation	imputation, macro variable, sample, proc step, call symput, macro loop	source	7
37	Householding and Its Relationship to Customer-to-Customer Marketing and Data Mining	Jacob Sacolick	Householding, the process of grouping customer account records and prospect lists forming decision units, is a prominent part of customer to customer marketing by financial firms. It allows the marketer to consider the entire relationship of the household to the financial institution and allows measuring customers for management and marketing reporting purposes. Complexity exists because a) several match criteria are used - some fuzzy matched, b) data may contain free format name/addresses with mixed personal/business names and c) householding may change over time due to external factors - divorce/marriage/death/birth or due to data/processing changes	data validation rules, do loop	source	8
38	How to Develop and Maintain a Corporate SAS Users Group	Bryan K. Beverly	One of the keys to building a successful SAS development shop is having an internal mechanism that guides all SAS-related activities; this mechanism is a corporate SAS users group. A corporate users group is different from the traditional users group in that: (1) it is the hub of company-wide SAS technical support, (2) it promotes individual and group professional development, (3) it participates in the recruitment and orientation of new SAS developers and (4) it works directly with management in exploring and exploiting new SAS-based revenue streams. This paper presents the methods and issues associated with developing and maintaining this type of SAS users group		source	2
39	How to Use the DATA Step Debugger	S. David Riba	All SAS 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: /G99 watch program logic execute /G99 examine variable values as they change /G99 repeat program statements /G99 jump to other sections of the `DATA STEP` /G99 modify DO loops interactively /G99 test for "dead" code /G99 give commands /G99 observe the results 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, macro variable, macro definition	source	9
40	Indexed Datasets 101	John Charles Gober	This paper is a shortened version of the paper presented at SESUG97 in Nashville under the title Understanding Indexed Datasets and Using Direct Access Queries. It will briefly introduce programmers to the bare minimum code needed to create and implement direct access processing through indexing. After reviewing this paper, the beginning to average programmer should have enough knowledge of the indexing process to be able to accomplish simple direct access queries which, under the proper circumstances, will save considerable processing time over using the customary merge routine. When to use Direct Accessing Retrieval by direct access is most efficient when a relatively small number of records from a transaction dataset need to be integrated or merged with an exponentially larger master dataset. For example, the Bureau of the Census conducts numerous non-decennial surveys for many of its sister agencies consisting of upward to several million participants	index creation, cpu time, sysrc	source	2
41	Let's Play a Game: A SAS Program for Creating a Word Search Matrix	Robert S. Matthews	This paper describes a process for inserting a list of words into a matrix of random letters. The output produces two tables. The first table is a display of the matrix after the words in the list are inserted, but before random letters are inserted into the remaining cells in the matrix. The second table is the final matrix after empty cells are filled with random letters. The program has three levels of difficulty and highlights a number of techniques for working with two-dimensional arrays. It is applicable to all versions and platforms of The SAS System		source	4
42	Macro Internals for the User - Developer's Overview	Susan M. O'Connor	You have used the macro language software that is part of base software from SAS Institute Inc. or you have inherited some SAS macros to support. Whether you have some working knowledge of the SAS macro facility or you have been afraid to change those legacy macros, some knowledge of macro internals would empower you to use macro with less anxiety. Just as you might be a more confident driver if you knew the internals of your automobile engine, you might be a more confident SAS macro user if you knew the internal details of the SAS macro processor. As a macro software developer, I have been conducting macro seminars in-house for our SAS testing groups, SAS quality assurance and SAS technical support. These sessions deal with macro topics and questions, and our SAS folks tell me that macro internal knowledge has helped them with writing and supporting their macros	macro variable, symbol table, local symbol table, macro definition, stored macro, macro facility, automatic macro variable, call symput, global symbol table, proc step, macro quoting function, autocall macro, macro trigger, macro put, macro parameter, missing value, proc print, macro loop, %if-%then-%else	source	14
43	Make Your Own Macro Processor	H. Ian Whitlock	A simple macro variable processor which one might call `SAS/PRETTYLOG` is implemented in a short and simple `SAS/GD2` program, PrettyLog.sas. The example provides a better understanding of how SAS macro works while solving the problem of making a pretty SAS log, i.e. indentation preserved log with resolved macro variables and no SYMBOLGEN mess. This utility only requires base SAS software and may be acquired at no more expense than a little learning effort	macro facility, macro variable, sas log, &variable, call execute	source	2
44	Managing the INTNX Function	H. Ian Whitlock	What is wrong with the INTNX function? INTNX moves by interval boundaries. Consider nxtbrtdy = intnx ( "year" , today() , 1 ) ; This produces January 1, 2000. Y2k compliant, but not exactly what I would like when today is a birthday and I want the next one. The same problem occurs for monthly increments. What's the answer? nxtbrtdy = %w_intnx ( "year" , today() , 1 ) ; What's the code? Come and find out. When was last Friday? That's simple, but it depends on a trick	datepart, sysdate9, %if-%then-%else, macro function, macro definition	source	2
45	Mapping: "Would You, Could You..."	Clara Louise Waterman	Managed Care Insurance has over 60 hospital and/or physician networks nationwide. As the number of networks grows, so does the necessity to develop graphic portrayal of the networks. PC `SAS/GRAPH` is used to produce maps of the networks by county for individual states as well as by national level. Benefits are realized through cost savings from the elimination of overlapping networks, and greater customer satisfaction due to expanding network services to contingent counties. The project started with the VP's request "would you, could you…"	proc step, proc sort	source	3
46	Matching Data Using SAS Programming and Human Judgment	Imelda C. Go	Matching data is not that difficult especially when reliable data is involved and when a computer does the matching. However, various problems arise when the variables used to match the data (e.g., social security numbers and names) are inaccurate. Even if computer-based algorithms are used to match most records, more records are sometimes found to match when a person reviews the data or uses human judgment. This paper describes the last stage of a matching process that requires human judgment. The unmatched data from two data sets are interleaved in an electronic data file that is inspected and revised by a person. The information in this revised file is used to find additional matching records that were matched based on human judgment	proc sort, proc step	source	3
47	No Program Is An Island: Passing Parameters to Tasks Launched by Servers and Schedulers	Michael L. Davis, Gregory S. Barnes Nelson	Many computer tasks are controlled and modified by parameters. They convey to our tasks information such as what range of dates to include, which reports to run, where to find the raw data, and sometimes whether an error has occurred that should cause suspension of the requested task. Parameters are one of the main means for tying tasks together to form applications. When using `SAS/AF` 1 and SCL, parameters can be passed along with CALL statements, through SCL Lists and SLIST catalog entries, parameter data sets and files, and through macro variables. This paper will explore and contrast examples of these techniques. Strategies to choose the best means for passing parameters to different types of successor tasks will be offered. When tasks are launched by a web server or a production scheduler, additional problems may emerge	macro variable, catalog entry, dataset, macro parameter, sas base, macro facility, data step, proc print, call execute, flat file, txt, macro call, date variable	source	10
48	Optimizing Data Extraction from Oracle Tables	Caroline C. Bahler	The `SAS/ACCESSÒ` product for OracleÒ offers a fast and easy interface for reading Oracle tables - access views or SQL Pass-Thru facility. However, if your extraction requirements include joining Oracle tables or extracting date ranges then you need to know Oracle's "flavor" of SQL. In addition, efficient use of `SAS/ACCESS` methods may require some knowledge of how the Oracle database was designed and what Oracle operational options are in effect. The objective of this paper is to discuss some of the potential pitfalls and efficiencies when working with `SAS/ACCESS` to extract information from Oracle. This paper assumes the reader is familiar with the `SAS/ACCESS` product and specifically targets `SAS/ACCESS` and Oracle operational and SQL options that can be used to optimize data retrieval. Extracting Data from Oracle ACCESS Views An Access view creates a "road map" to the location of a table and permits data extraction to occur. Access views are created using `PROC ACCESS`	proc sql, proc step, macro variable, dataset	source	8
49	Optimizing SAS Software on Windows NT: A Guide to Performance Tuning Your Applications Server	Peter Parker	Optimizing SAS software from the perspective of an applications programmer requires writing efficient and clever code. However, here I'll re-examine my computer system with a systems administrator's eye. I'll be more concerned with the speed and the efficiency of the hardware and the operating system, Microsoft Windows NT 4.0, as it runs SAS software. Optimization is making the computer system run faster by minimizing bottlenecks. Running SAS software to manipulate large data sets and to crunch vast amounts of numbers puts a significant load on a computer. Any system improvements would produce faster query and report turn-around, creating a more efficient office	elapsed time, proc step	source	9
50	Programming Solutions with SAS Formats and Informats	Imelda C. Go	Formats and informats are programming tools that can simplify programming tasks. This paper demonstrates how these tools can be used to more easily accomplish certain tasks. The solutions these tools provide are simple; result in an economy of code; increase the readability of programs; and take advantage of built-in SAS features that facilitate data processing, reporting, and general programming. Topics covered include recoding and look- up tables	proc step, proc format, proc means, proc print, character variable, format statement, numeric variable, char., lookup, input statement, data cleaning, proc freq, proc sort	source	9
51	Providing Web-Based Support for SAS Users at NC State University	Joy Munk Smith	Developing a website to support our SAS users requires time and research, but it is worth the effort. Our clients began using the website while it was still in its infancy. In this paper we report what we are learning about design concepts that increase attractiveness, usability, accessibility, visibility, ease of development, and ease of maintenance (ouch!). We are not experts, but we want to share experiences with others involved in developing similar sites	sample, likelihood function	source	6
52	Pruning the SASLOG - Digging into the Roots of NOTEs, WARNINGs, and ERRORs	Andrew T. Kuligowski	"Look at your `SASLOG`." You hear it from instructors of courses related to the SAS System. You read it in papers that are published in the Proceedings of SESUG and other similar conferences. But they never seem to address the next obvious issue - "Then what?" What should you be looking for? And what should you do if you find it? This presentation will look at one message that is often found in the `SASLOG`: NOTE: `MERGE` statement has more than one data set with repeats of BY values. We will discuss - and quickly discount - a "bandage" approach that w ill stop the mess age from being displayed. More importantly, we will discuss the creation of an ad-hoc routine that will help you understand why the message occurred, and how to revise your code to prevent its recurrence. `MERGE` Statement: Repeats of BY Values Most users of the SAS system have encountered the following message: NOTE: `MERGE` statement has more than one data set with repeats of BY values	proc step, merge statement, numeric variable, out=, proc means, dataset	source	8
53	Recent Advances in Categorical Data Analysis	Maura E. Stokes	The last fifteen years have brought many changes to the practice of categorical data analysis. This pa- per reviews some of the major changes and shifts of emphasis and discusses several examples using SAS software procedures. Topics include the use of exact methods, generalized estimating equations, conditional logistic regression, and current uses of weighted least squares modeling. Applications pro- vide illustration for many topics. This paper describes software currently available in the SAS System and indicates the areas in which new software should be available in the next few years. The references in- clude some pertinent methodology and review pa- pers		source	11
54	Removing Macro Variables from the SAS Environment	Frank C. DiIorio		macro variable, options statement, symbol table, %if-%then-%else	source	3
55	SAS Client-Server Development: Through Thick and Thin and Version 8	Eric C. Brinsfield	SAS Institute has been a leader in client-server technology since the release of `SAS/CONNECT` software and the `SAS/ACCESS` Pass-Through Facility. With the release of Version 8 and new developments in the database and telecommunications industries, client-server applications have moved into the next generation. This paper will explain the principles of good client- server design with a specific focus on SAS application development, thin-client architectures, and three-tier optimization. In addition, the paper will cover how client-server design options differ between Version 6 and Version 8 of SAS software		source	7
56	SAS Components To Help You Survive A Deserted Island	Stephen M. Noga	You are alone on a deserted island (your job) and can only use four components of the `SAS/GE2` system to get your job done. What four components would they be, and why? Because of how expansive the SAS system is, sometimes programmers spend more time looking for a procedure to do a particular task than utilizing what they know to do the same thing. This paper will demonstrate that with a good working knowledge of only four components (all contained in Base SAS) out of the entire SAS system, roughly eighty to ninety percent of all tasks can be accomplished	proc step, proc sort, data step, proc means, proc univariate, proc freq, if-then-else	source	7
57	SAS I/T Service Vision, Delta Technology's Performance Database	Bob Chaney	Managing Enterprise-wide capacity and performance in an n-tier environment is the challenge facing capacity planners and performance analysts today. This challenge is being met by Delta technology, Inc., Delta Air line's wholly owned I/T subsidiary, by creating Performance Data Bases (PDBs) with SAS I/T Service Visionä software. The project to identify the best Enterprise-Wide PDB product assembled a cross-functional team from OS/390, UNIX, Network and NT Server departments. Choosing I/T Service Visionä has allowed Delta Technology to not only begin defining the capacity of the Enterprise, but also to save operating costs by replacing the more expensive and less functional CA-MICSä product suite	proc means, capacity planning	source	4
58	SAS Skills for the Next Millennium A Geek Peek into the (not so distant) Future	Gregory S. Barnes Nelson, Jodi Barnes Nelson	Whether you are a new SAS user, an accomplished developer or a manager responsible for recruitment and selection of SAS talent, you will be interested in this look at what it takes to be a SAS programmer in the Year 2000 and beyond. It is a compendium of quotes and commentary for SAS programmers (or anyone for that matter!) to think about that helps you focus on what skills will be in demand. Most of this paper is centered on non-technology specific concepts, although there is some discussion about specific SAS skills we think employers, clients and partners will seek	sas programmer, data warehouse	source	10
59	Seven Steps to SAS/GRAPH Savvy	Neil H. Howard	Adding color graphics to your reporting repertoire can maximize the impact of your data analysis. This tutorial provides the basics for effectively making the move to `SAS/GRAPH`. Take advantage of the `SAS/GRAPH` procedures by following the author's seven essential steps: 1) know your data, 2) know your intended results, 3) understand how to communicate effectively with graphics, 4) know your product - defaults and basics, 5) experiment with advanced features and options, 6) edit your graphics, and 7) test your results. The author will solve basic problems using vertical and horizontal bar charts, pie charts, plots and maps. The techniques will address categorical and continuous data. The code examples start simply, add features, and demonstrate options. Take away an enhanced appreciation for information visualization. The published abstract and introduction provide the philosophy and basics. A color handout of the data, code, and graphics w ill be available for session attendees	horizontal bar chart, bar chart	source	2
60	Shortcuts	Janet E. Stuelpner	There are many ways to write a variable list. Of course, you can list every variable, which requires a great deal of typing, if you have a large number of variables. However, there are some shortcuts. This paper will discuss several ways within the base SAS product to cut down on the amount of typing that is usually done when listing variables	variable list, name range list, numbered range list	source	2
61	So Many PROCs, So Little Time: A Primer of Efficient Report Writing in Base SAS	Deborah B. Buck	Almost any report can be generated in at least two ways using SAS software, and almost every report can be written using the `DATA STEP` report writing capabilities (using the FILE-PUT mode), but why reinvent the wheel if a `PROC` already exists that will give you the desired report with a minimal amount of effort? This presentation will explore various common types of reports and what factors you should consider in deciding which procedure is best suited to your needs. It is not meant to be a detailed guide about `PROC` statement coding, but rather a guide on how to decide which procedure fits the needs of a given situation. Examples will be presented of differing types of reports with	proc step, proc print, proc report, proc tabulate, sas base	source	9
62	Statistical Presentations Using the Power of PROC TABULATE	C. Olivia Parr Rud	`PROC TABULATE` is a versatile tool which can combine the functionality of `PROC MEANS` and `PROC FREQ`. Additional power exists in its ab ility to perform analysis on grouped data. This paper details the steps for constructing a table of marketing statistics using a variety of features. Missing values and formats are used to control the table's calculations. Labeling and selected options provide finishing touches for controlling the table's appearance	proc step, proc tabulate, fee income, interest, proc format, proc freq, sample, label statement, credit card, missing value, interest rate, sample size	source	8
63	Statistics Without DATA _NULLS_	Michael C. Palmer, Cecilia A. Hale	Analysts attracted to SAS for its statistical capabilities no longer have to settle for its clumsy publishing capabilities. Instead, they can take advantage of the Output Delivery System (`ODS`) in version 7.0, SAS's data warehouse and data processing capabilities, and a new open-source, non-proprietary software technology, and literally never use a DATA `_NULL_`, `PROC REPORT`, or `PROC TABULATE` again. An analyst working with publishing software and exploiting its layout and styling flexibility creates a terse sample table. The sample, via SAS programs, directs the retrieval of data from a warehouse and the creation of publishable markup. The publishing software renders the markup publication ready without re-typing, cutting-and-pasting, or format conversion of SAS output. The new, platform- independent software technology is eXtensible Markup Language (XML). Statistical analysts and their organizations will better exploit the strengths of SAS and publishing software by coupling the two via	proc tabulate, sample, data science	source	6
64	Tech Report 2000: Telecommuting with SAS Saves Gas The SAS Application Developer's Guide to the Virtual Office	Eric C. Brinsfield	Due to advances in technology, economic necessity, and corporate acceptance, telecommuters have grown in number significantly over the last few years. This trend will continue, but obstacles do remain for the trek toward widespread virtual offices. This paper will address the technical, social, economic, and SAS-related issues that all telecommuters or managers of telecommuters must consider before committing to the virtual office environment. SAS software includes many tools that make SAS application development in the virtual office possible, but SAS Version 8, as well as other software and hardware advances, are changing our virtual world	macro variable, parallel processing	source	8
65	Telecommuting: The Workplace of the 90's	Thalene T. Mallus	The federal government, like industries in the private sector, has the ability to offer its employees flexible work arrangements. One arrangement which is becoming increasingly popular is telecommuting, where employees work for a portion of the week from home or an alternate remote location. As computer awareness, network access, and the World Wide Web are adopted into the mainstream, more and more employees in both the public and private sectors are finding that the tools necessary to successfully telecommute are easily within their reach. Although not every occupation is compatible with telecommuting, SAS programmers in particular can benefit from a variety of resources which allow remote access to data and programs	web service, isp	source	9
66	Tessera Rapid Modeling Environment: Production-Strength Data Mining Solution for Terabyte-Class Relational Data Warehouses	Michael Nichols, John Zhao, John David Campbell	Profitability for leading corporations depends on increasing revenue while containing advertising and marketing costs. In an effort to acquire a complete customer profile, many organizations have created large, customer-centric relational databases. After compiling and centralizing customer data, companies are faced with the challenge of translating volumes of customer data into knowledge that can be acted upon. To maintain a competitive edge, marketing analysts need to be able to access and interpret customer information accurately and efficiently. With Tessera's Rapid Modeling Environment (RME), companies can develop applications quickly so that marketing analysts can access and interpret customer information on an ad-hoc basis. Tessera's RME improves an organization's overall analytic capabilities such as segmentation, profiling, and scoring. Unlike data mining tools on the market today, Tessera's RME lets analysts perform scheduled production scoring against the full customer base. In addition, analysts can capture generated scores and write them back to the marketing database.	sample, proc sql, model deployment, data mining, dataset, data warehouse, relational database	source	9
67	The Power of SAS Input Statements	Imelda C. Go	SAS can process data in a variety of forms. If the input data occurs in a predictable form or pattern governed by a set of rules, input statements can be written to process what would otherwise seem like irregular (and unusable) data. Examples include delimited data, text qualifiers, headers, multiple records per line, multiple lines per record, and conditional input statements	input statement, proc print, list input, column input, proc step	source	3
68	The SAS Debugging Primer	Frank C. DiIorio		proc step, macro variable, input statement, proc print, automatic variable, proc sql, put statement, regression analysis, proc freq	source	5
69	The Writing for Reading SAS Style Sheet: Tricks, Traps & Tips from SAS-L's Macro Maven	Ronald J. Fehd	A program is a form of communication that occurs in two distinct and vastly different events: the first event is immediate: when the program is submitted to the language processor for execution; the second event takes place at a later time: when the writer or another programmer returns to read that program for maintenance. A good style sheet can facilitate program maintenance. This is especially important when simultaneously writing in two languages: SAS and it's macro language. This paper discusses elements of a style sheet for SAS programmers. The intended audiences are intermediate SAS programmers and beginning macro programmers	macro facility, macro variable, %if-%then-%else, macro definition	source	4
70	Those Missing Values in Questionnaires	John R. Gerlach, Plymouth Meeting	Questionnaires are notorious for containing responses that later become missing values during processing and analyses. Contrary to a non-response that	missing value, inputn, if-then-else	source	6
71	User-Specified Text Flow Inside The Report Procedure	Donald Peterson, John R. Gerlach	The FLOW option of the `REPORT` procedure in SAS allows the user to include lengthy text in a report by wrapping the text within a specified column width. This powerful feature splits the text using the so-called split character, as well as the blank character. The text is always left justified, not allowing any kind of indentation, unless you insert blank characters accordingly, which is very tedious. This paper explains the %flowvar macro that modifies the character variable allowing the FLOW option to produce indented text, beginning after the first line for each observation in a report	proc report, character variable, proc step	source	3
72	Using JMP for Technical Analysis of Stocks in Highly Volatile Markets	William R. Gjertsen	We live in a world of high uncertainty. Internet related stocks that appreciate 300% with no earnings to report have, in some instances, lost 25% in value in the morning and rebound to positive ground before the close! Some day traders are having a field day and are saving the airfare to Las Vegas! Others of us need some sensible rules of when to sell and when to buy. Technical Analysis (i.e. trend lines and oscillators) when properly tuned can help us establish sensible trading rules. This paper shows how you can generate and test your own trading rules with JMP	moving average, excel	source	7
73	Using SAS ARRAYs: An Introduction to Easy Recodes	Francis J. Kelley		array, macro variable, sas programmer, proc step	source	3
74	Using SAS Software to Analyze Sybase Performance on the Web	Joseph Mirabal Zhengyu Wang	This paper provides a web-based system using SAS, HTML and CGI/PERL to provide rudimentary and complex Sybase DBMS performance metrics for Unix based system operations. Sybase SQL Server performance data is collected by Sybase Historical Server allowing for the collection of performance information with minimal impact on the server. The SAS System (Base SAS, Macro, STAT and `SAS/GRAPH`) is especially well suited to analyzing and visualizing these data. Its graphical, data mining and statistical capab ilities coupled with its ability to a ccess data from a multitude of formats, including DBMS, PC and ASCII files, provides an all in one performance analysis toolkit. In this paper, we present a World Wide Web interface to exploit the power of SAS processing for open system delivery of information. The SAS system processes calculations much faster than the functions supplied with DBMS technology	proc sql, sql server, call symput, macro variable, flat file, relational database, sas programmer, macro definition, data step	source	5
75	Using SAS to Perform the Analysis of Means for Variances Test	Peter S. Wludyka	The Analysis of Means for Variances (ANOMV) is a method for testing the equality of K variances from normal populations. The test can be performed by creating a decision chart that resembles a Shewhart control chart. Should any of the K sample variances (or equivalently, standard deviations) plot outside the decision limits the homogeneity of variances (HOV) hypothesis is rejected. Using the ANOMV decision chart allows practitioners to assess both statistical and practical significance. After a brief description of the ANOMV test, SAS code (a Macro) for generating an ANOMV decision chart and related output for balanced designs is presented. The MACRO will also produce an Analysis of Means (ANOM) decision chart	sample, standard deviation, sample size, degrees of freedom, class variable, %if-%then-%else, macro definition	source	6
76	Using SAS, SAS/ACCESS, and SQL Passthrough to Query and Join ORACLE Tables: An Example Using the Health Care Finance Administration's SDPS (Medicare) Database	Barbara B. Okerson	Medicare Encounter data is received by each state's Peer Review Organization as an Oracle database known as the SDPS (Standard Data Processing System) data set. This data set is used for quality improvement projects, integrity investigations, and research. This data set is then queried with SAS software and the SAS SQL pass-through facility. Often the criteria for selecting data from the SDPS data set are contained in a pre- extracted SAS data set. Using the criterion information from the SAS data set, additional data is extracted from the SDPS database and merged or combined with the existing SAS data set or its information. In this example used to document comorbidities and disease progression for HIV, a SAS data set is run against the SDPS Oracle database to obtain subsequent admissions and diagnoses for each patient (Medicare beneficiary). This paper illustrates four methods for performing this query using `SAS/ACCESS`, `SAS/CONNECTÂ` , and `PROC`	dataset, proc sql, macro variable, oracle, cpu time, macro definition, macro facility	source	5
77	Using SAS/AF to Create Applications for the Administrative Aspects of Data Management in Clinical Trials	Emily A. Mixon, Karen B. Fowler, Felicita David	`SAS/AF` Frame applications enable the data manager to maintain patient randomizations and case report forms (CRFs). The user is able to create patient calendars, generate monthly expected visit reports, and maintain logs of CRFs received for a patient at any given study visit. These administrative tasks are easily accomplished with the use of a `SAS/AF` application. Upon randomization into the clinical trial, the user is able to generate a patient calendar projecting the dates for all the study visits required by the protocol. The information generated by the patient calendar is used by another `SAS/AF` Frame entry to generate expected visits for intervals chosen by the user. A `SAS/AF` Frame entry for receipt of CRFs for data entry was developed listing CRFs required for a study visit with check boxes for forms received. Using the information from the CRFs receipt frame, missing or delinquent CRF reports may be generated	visit, randomization, dataset, crf, clinical trial, proc step, proc print	source	4
78	Using SAS/AF to Create Data Entry Screens with Multiple Comment	Fields Allowing	This paper describes a process, using `SAS/AF` software, for creating data entry screens that can contain multiple comment fields. An unlimited amount of text information can be stored in each field and there can be an unlimited number of comment fields for each observation. The comment fields are defined as 'Extended Text Entry' widgets in an AF Frame screen. The text information in the comment fields is stored in a SCL List that is then saved to, and retrieved from, a SAS catalog entry. A SAS dataset is used in conjunction with a SAS catalog to provide a complete data entry system. The intended audience for this paper should have an intermediate level of knowledge about the Base SAS System as well as proficiency using `SAS/AF` and Screen Control Language	catalog entry, catalog, dataset, character variable	source	4
79	Using the SAS System to Examine the Agreement between Two Programs That Score Surveys Using Samejima's Graded Response Model	Jim Penny	In the Spring of 1998, researchers at the Center for Creative Leadership chose to use the Graded Response Model by Samejima as part of a project to assess the behavioral changes that are seen in the participants in the leadership development programs of the Center. It was determined that the existing DOS and Windows software would not function with sufficient reliability within the extant computing network of the Center, and a contract was awarded to a vendor for the development of scoring program that would operate reliably at the Center. As a part of the contract specifications, the Item Response Theory parameter estimates of ability and standard errors that were produced by the new computing module had to agree with those estimates produced by the existing software. As one might expect, it was difficult to demonstrate exact convergence of the two sets of estimates. This paper presents the statistical process by which the case for sufficient convergence was made	proc calis, sample, output delivery system, bar chart, sample size, logistic distribution	source	7
80	Utilizing SAS Software in the Evaluation of Virginia Tech's Academic Eligibility Policy	Kristen H. Bush	Beginning in Fall of 1997, freshmen entering Virginia Tech were required to maintain a 2.00 grade point average to be considered eligible for continued enrollment in the University. This policy was adopted to promote a higher level of academic achievement for Virginia Tech students. However, it was expected that the policy would negatively impact student retention, especially freshmen retention. A study investigating the effects of the Academic Eligibility Policy on student retention was initiated. The populations of interest were freshmen who entered the University prior to the implementation of the new policy and freshmen who entered after implementation of the new policy. The 1995 and 1996 freshmen were considered as samples of the first population and the 1997 freshmen were considered as samples of the second population. Two performance measures were identified: end of the second Fall semester GPA, and the percentage of students returning for their second fall semester	null hypothesis, predictor variable, population, proc step	source	6
81	What's New in Versions 7 and 8 for SAS Files?	Jane Stroupe	The Nashville Release of the SAS System provides several new features and enhancements to SAS files and their structure. As you begin to use the Nashville release, an understanding of compatibility between Version 6 SAS files and Nashville SAS files, along with the knowledge of what's new in the Nashville release, can assist in making the decision of when to make the change. This paper is an introduction to those features	proc step, audit trail, constraint, foreign key, key, proc print, dataset, libname statement, create table, proc sql	source	6
82	Year 2000 Triage For Your SAS Applications	Mike Kalt	You had every intention of finishing all of your Year 2000 testing and remediation early and spending January 1, 2000 lying on the beach. But it's just a few months before the millennium and you still haven't tested your SAS applications! Even if you don't have time to do complete testing of all of your SAS applications there are a number of things you can do to find and eliminate potential problems. This paper will discuss the most effective techniques for evaluating your SAS applications and making them compliant in the shortest amount of time. Some of the topics to be covered include: Tools to locate potential problems in your SAS applications What to look for when testing your SAS applications Testing your applications in a Year 2000 environment Using the YEARCUTOFF= option to handle two-digit years	date variable, sysdate9, proc step, dataset, raw data, character variable, proc sql, sas log, catalog entry, excel, data cleaning	source	7
83	YOUR FRIEND THE COLON:	S. David Riba	There are many techniques that can be used when comparing or selecting character data. One of the most useful is also probably one of the least known. When used to modify comparison operators, the colon ( : ) can greatly improve the flexibility of the comparison operator while considerably simplifying the resulting SAS program code. This modifier has been part of Base SAS since the days of Version 5 or earlier. This paper will review some typical uses where the colon modifier can improve on traditional programming methods when comparing or selecting character data	colon modifier, substr function	source	2

Back to Conf go 2000 go 1998

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.