MWSUG 2005 Papers - Index

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

#	Title ×	Authors ×	Abstract ×	Keywords ×	Pages
1	44 Tricks with the 4mat Procedure	Ben Cochran	Actually, there probably are not a to tal of 44 tricks that one can do with the `FORMAT` procedure. The number was chosen purely for the purposes of alliteration. However, there are some fairly powerful things one can do with this procedure, and this paper serves as a gentle introduction to the `FORMAT` procedure. In SAS, a format is simply instru ctions on how to write or display a value. There are dozens, if not hundreds, of formats that ship with the SAS system. While they cover many of the user's needs, they cannot possibly cover all of them. So, the SAS System includes a tool that allows users to create their own formats. That tool is the `FORMAT` procedure	proc step, proc format, format statement, proc freq, proc print	7
2	A Case Example Of SAS/IntrNet With Java Script	Desheng (Ben) Xu	In SAS web applications, the parameters are passed to the Application Dispatcher to process. By using JavaScript, the parameters can be dynamically passed to the CGI broker. Also this paper addresses how to build index for SAS data set to speed up the application. In addition, the session concept is applied in the application. This paper is appropriate for intermediate programmers who know `SAS/INTRNET` as well as JavaScript language	dataset, proc step, macro variable	6
3	A Comparison Of Linear Mixed Models To Generalized Linear Mixed Models: A Look At The Benefits Of Physical Rehabilitation In Cardiopulmonary Patients	Jennifer Ferrell	The focus of this paper is to compare mixed models and generalized mixed models using a clinical database. Generalized linear mixed models (GLMMs) allow the error term to include the exponential family, and can incorporate repeated measures and random effects. Since generalized mixed models are a fairly new concept, they have been used sparingly in healthcare research. SAS has a new procedure (GLIMMIX) for the generalized mixed `MODEL` procedure. The different methods will be compared in the context of studying rehabilitation provided to patients with chronic illnesses. Currently, Medicare does not consider cardiopulmonary needs as a rehab classification. The purpose of the study is to show that patients with chronic illnesses receive the same benefits from physical therapy, as would a person with orthopedic problems. Using an existing data set of 556 records, the different models in SAS were used to analyze the data with respect to patient diagnoses and severity of symptoms	proc mixed, proc glimmix, proc glm, fixed effects, proc model, proc genmod, proc step, correlation, sas enterprise guide, residual, insurer, estimate, data mining, covariance, proc freq, response variable	7
4	A Macro For The Calculation Of Age, Gender And Race Adjusted Incidence And Mortality Rates	Padmini Sekar	Two aims of population based studies are to report mortality rates and incidence rates of diseases. This macro was developed by expanding a methodology of an earlier report to calculate age and sex adjusted rates. It now allows the calculation of age, race and sex adjusted rates. The macro was originally developed to calculate incidence rate of strokes in the five county regions in the Greater Cincinnati area. Since there was no established methodology to calculate rates in biracial populations such as this, we devised a macro to calculate an age, race and sex adjusted rate. It is now being used to calculate lung and other cancer mortality rates in the state of Ohio. The variance is estimated assuming that the incident cases follow a Poisson distribution. Therefore, the macro can be used if the incidence rates are less than 10% in the population	proc calis, poisson distribution, binomial distribution, confidence interval	12
5	A Primer For Creating a Usable Database in SAS	Frank A. Ferriola	Companies today drive key business strategy from the analysis and reporting of corporate data. Using data with integrity checks improves the outcome of this strategy along with eliminating the pitfalls of determining which report is the truest measure of the company's operations. By addressing gaps in the data and fully populating all fields, organizations can create centralized databases giving them a "single version of the truth." This presentation overviews the strategy and standards used by a major financial services organization in deploying databases utilizing SAS Software. We will look at building databases with integrity checks and review the steps for taking inventory of the data, defining/re-defining its use, and populating fields. These practices ensure the construction of "single version of the truth" databases providing organizations with credible information to drive successful strategies	data dictionary, financial services	5
6	A Recipe For Success - Migrating SAS/AF Applications To The Web Using SAS, HTML And JavaScript	Jonah P. Turner	The Internet is a widespread information network that has reformed organizational structures and transformed business strategies. Given the predominance of cross-platform, global clientele and the ever-increasing need to deliver information, it serves great value for organizations to exploit Web technologies. SAS programmers can adapt to these modern technologies by retooling their app lications to provide clients with more accessible, user- friendly Web-based solutions. Specifically, by drawing on various Web programming techniques, a developer can seamlessly rework a `SAS/AF` program into an application that functions via the Internet	ods html, macro variable	9
7	An Overview Of The Data Mining Program At The University Of Central Florida	Morgan C. Wang		data mining, loss cost, traffic data	25
8	Arrays Made Easy: An Introduction to Arrays and Array Processing	Gerald D. Frey	Many programmers often find the thought of using arrays in their programs to be a daunting task, and as a result they often shy away from arrays in their code in favor of better-understood, but more complex solutions. A SAS array is a convenient way of temporarily identifying a group of variables for processing within a `DATA STEP`. Once the array has been defined the programmer is now able to perform the same tasks for a series of related variables, the array elements. Once the basics of array processing are understood arrays are a simple solution to many program scenarios. Throughout this paper we will review the following array topics: 1) Why do we need arrays? 2) Basic array concepts a) Definiti on b) Eleme nts c) S yntax d) Rules 3) Using array indexes 4) One dimension arrays 5) Multi-dim ension arrays 6) T emporary arrays 7) Explicit vs. implicit subscripting 8) Sorting arrays 9) When to use arrays 10) Common errors and misunderstandings	data step, array, temporary array, numeric variable, array bounds, variable, character variable	9
9	Avoiding Mouse Elbow	Malachy J. Foley	Computer programming or coding may literally be dange rous to your health. Mouse Elbow, which is akin to Tennis Elbow, is just one adverse health c ondition that is associated with computer use. Other maladies associated with computers include Carpal Tunnel Syndrome (from keyboard and the mouse), shoulder and neck pain, and Sciatica. This paper describes computer-related health risks with special emphases on musculoskeletal disorder (MSD) and Mouse elbow. The information in this paper will hopefully help y ou avoid computer-related injury, or detect and cure it at an early stage		7
10	Boost Your Programming Activity With SAS Enterprise Guide	Chris Hemedinger	SAS Enterprise Guide (with its easy-to-use interface) has been a boon to SAS users, especially non-programmers. However, SAS Enterprise Guide provides some powerful new features that are geared toward the SAS programmer, including an integrated process-flow view of your project; the ability to create, publish, and execute stored processes; and increased flexibility for output format and des tination with the SAS Output Delivery System (`ODS`). This paper provides an overview and detailed examples of how SAS programmers can leverage SAS Enterprise Guide to create, organize, and execute their SAS programs	sas enterprise guide, sas enterprise guide project, macro variable, sas programmer, sas programming, bar chart	9
11	Building and Using User Defined Formats	Arthur L. Carpenter	Formats are powerful tools within the SAS System. They can be used to change how information is brought into SAS, how it is displayed, and can even be used to reshape the data itsel f. The Base SAS product comes with a great many predefined formats and it is even possible for you to create your own specialized formats. This paper will very briefly review the use of formats in general and will then cover a number of aspects dealing with user generated formats. Since formats themselves have a number of uses that are not at first apparent to the new user, we will also look at some of the broader application of formats. Topics include; building formats from data sets, using picture formats, transformations using formats, value translations, and usi ng formats to perform table look-ups	proc format, proc step	9
12	Calculation Of Health Disparity Indices Using Data Mining And The SAS Bridge To ESRI	Mussie A. Tesfamicael	Socioeconomic indices are strongly believed to be associated with the risk of disease. However, no consensus exists in the US regarding which area-based measure should be used to measure or monitor socio-economic inequalities in health. The purpose of this paper is to determine which area-based socioeconomic measures would be most appropriate for US public health surveillance to investigate in relationship to the incidence of disease. Geographic information systems (GIS) manage, analyze, and disseminate spatial data. Arc Map is used to display results of the analysis in a variety of formats, such as maps, reports and graphs. The SAS Bridge to ESRI is used to transfer the spatial information directly into SAS datasets. The specific example here is to examine the relationship between the rate of cancer and the various indices of social economic (SES) conditions for the study area consisting of Kentucky, Tennessee, North Carolina, Virginia and West Virginia	factor analysis, predictor variable, interaction effect, proc glm, cluster analysis, dataset, outlier	9
13	Comparison Of Enterprise Miner And SAS/STAT For Data Mining	Patricia B. Cerrito	There are many definitions of data mining: the discovery of spurious relationships in the data; automated data analysis; examination of large data sets; exploratory data analysis. Early methods of data mining included stepwise regression, cluster analysis, and discriminant analysis. Data mining should be thought of as a process that includes data cleaning, investigation of the data using models, and validation of potential results. In particular, practical significance should be emphasized over statistical significance. Also, decision making and the cost of misclassification is important. `SAS/STAT` contains methods that can be used to investigate data using a data mining process. These methods can complement those developed specifically for Enterprise Miner, and can be used in conjunction with Enterprise Miner. This paper will examine data mining in `SAS/STAT`, contrasting it with Enterprise Miner	data mining, sample, proc step, regression analysis, proc hpsplit, logistic regression, logistic distribution, data cleaning, discriminant analysis, neural network, histogram, cluster analysis, proc cluster, proc fastclus, data science, response variable, training set, proc sort	12
14	Creating Zillions of Labels (and Other Documents) the Easy Way with ODS and Microsoft Word	Vincent DelGobbo	This paper provides a quick and easy way to generate address labels or other data-driven documents from your SAS data. The first step is to use the SAS Output Delivery System (`ODS`) to convert your data into a format that Microsoft Word can import. Then you use Word's Mail Merge Wizard to guide you through the steps to create your document. The technique is easy, requires only Base SAS version 8 or later, and will work on any platform where SAS is installed (even if SAS is installed on a mainframe). This technique can also be used with SAS version 6 by using the SAS HTML Formatting Tools instead of `ODS`	dataset, sample	5
15	Customizing ODS Statistical Graphs	Cynthia L. Zender, Catherine Truxillo	Have you heard about `ODS` Graphics or seen some of the demos? If you are a statistician interested in obtaining easy graphics from statistical procedures, `ODS` Graphics features provide an automated way of exploring statistical results with a picture. However, if you are a SAS programmer interested in customizing the plots automatically produced by `ODS` Graphics, you can benefit from an understanding of the graph and style templates that SAS provides for these plots, especially to make changes that persist from one application to the next. Follow the authors on a journey of discovery with `ODS` Graphics, as they explain how to access and modify graph templates. By the end of the presentation, which includes code samples and demos, you will have a better understanding of the relationship between statistical procedures, graph templates, style templates, and DATA `_NULL_` programs. The authors take you through every step of their discovery process	proc princomp, proc step, proc template, macro variable, ods html, sas log, proc sgplot, graph template language, title statement, sas programmer, select, output delivery system	22
16	Information Discovery Using Decision Trees	Morgan C. Wang		regression analysis, proc hpsplit, interval variable, data cleaning, sample, data mining, factor analysis	79
17	Introduction To SAS Business Intelligence/Enterprise Guide	Alex Dmitrienko	This paper provides an overview of new SAS Business Intelligence solutions, including Enterprise Guide, Add- in for Microsoft Office and Web Report Studio, and provides a detailed description of the most popular of them, Enterprise Guide. Enterprise Guide has attracted much attention in the SAS user community because it offers an intuitive point-and-click interface and provides the user with a large number of standard data manipulation/summary tools. This paper introduces the latest version of Enterprise Guide (Release 3.0) as well as the new version that will be rolled out later this year (Release 4.1). It summarizes main features of this product such as Enterprise Guide tasks, project-centered programming, etc. This paper also demonstrates how SAS users can efficiently transition to the user-friendly environment provided by Enterprise Guide and increase their productivity by taking advantage of its unique tools	sas enterprise guide, business intelligence, dataset, character variable, excel, format statement, macro definition, raw data, proc step, sas log, proc means, proc freq, histogram	13
18	Macro Functions: How to Make Them - How to Use Them	Arthur L. Carpenter	The SAS macro language includes a number of macro functions, such as %UPCASE, %QSCAN, and %SUBSTR. In addition a number of Autocall macros, such as %LEFT, %TRIM, and %VERIFY, are also supplied that act like macro functions. Macro functions are especially useful as programming tools, because the function call is replaced directly by the result of the call. Many macro programmers are unaware that they too can write useful macro functions. Fortunately macro functions are not difficult to program. Not difficult, that is, if you know the simple techniques required to turn a macro into a macro function. This paper shows you how to create a macro function, the statements that you must avoid, and the technique used to "pass" the result of the function back to the calling program	macro function, macro variable, macro definition, macro call, macro facility, %if-%then-%else, symbol table	6
19	Medicare Cost Estimation For Heart Disease	Fariba Nowrouzi	The objective of this paper is to examine information about Medicare costs for the treatment of heart disease by using information from a Medpar database (the public-reporting billing forms used by Medicare). The database contains 4862 patient records related to treatment of the heart. The purpose is to examine the relationship between reimbursements, treatments, length of stay, and patient severity. Kernel density estimation demonstrates that the distributions are exponential or come from an exponential family. Because patient severity depends upon the uniformity of data entry, all assumptions of linear and logistic models are violated, putting into question the validity of hospital quality rankings. Reimbursements are also dependent upon the accuracy of data entry. The problems with validity will be demonstrated using SAS data mining techniques	anova, proc mixed, null hypothesis, predictor variable, response variable, proc anova, normal distribution, proc step, correlation, proc glimmix, pearson correlation, probability distribution, fixed effects, standard deviation, proc genmod, sas enterprise guide	11
20	MERGING vs. JOINING: Comparing the DATA Step with SQL	Malachy J. Foley	Which merges files b etter: the SAS `DATA STEP` or SAS SQL? Traditionally, the only way to merge files in SAS was via the SAS `DATA STEP` . Now SAS pro vides a Structured Query Language (SQL) facility wh ich also merges files. This tutorial compares and contrasts these two merge facilities. It examines the pros and cons of each merge technique. It looks at `DATA STEP` code to perform specific merges and then looks at the corresponding SQL code to perform the same merges	proc sql, inner join, full join, create table, proc step, right join, where statement, coalesce function, data merging, relational database, merge statement	17
21	Mining Transactional And Time Series Data	Michael J. Leonard	Web sites and transactional databases collect large amounts of time-stamped data related to an organization's suppliers and/or customers over time. Mining these time-stamped data can help business leaders make better decisions by listening to their suppliers or customers via their transactions collected over time. A business can have many suppliers and/or customers and may have a set of transactions associated with each one. However, the size of each set of transactions may be quite large, making it difficult to perform many traditional data-mining tasks. This paper proposes techniques for large-scale reduction of time-stamped data using time series analysis, seasonal decomposition, and automatic time series model selection. After data reduction, traditional data mining techniques can then be applied to the reduced data along with other profile data. This paper demonstrates these techniques using `SAS/ETS`, `SAS/STAT`, Enterprise MinerTM, and SAS High-Performance Forecasting software	time series analysis, sample, time series data, data mining, seasonal decomposition, cluster analysis, proc freq, proc hpsplit, series plot, distance measure, feature selection, correlation, heatmap, seasonality, dimensionality reduction, estimate, missing value, proc calis, proc cancorr, outlier	26
22	Relationship Between Total Charges And Reimbursements In Outpatient Visits Using SAS GLMMIX	Chakib Battioui	The purpose of this paper is to examine the use of different statistical tools to investigate data concerning outpatient visits in a hospital setting. The specific objective is to examine the relationship between the total charges billed by a hospital compared to the payments received for outpatient care. The data were derived from the 2002 Medical Expenditure Panel Survey (MEPS), containing 20,488 outpatient event records. Kernel Density estimation was used to examine the distribution of the total charges compared to reimbursements. Results show that the two distributions are not normal. There is also a shift of cost between the two, a shift that must be paid by the healthcare provider instead of the insurer. The Generalized Linear Mixed Model (GLMMIX) was used to investigate the shift between charges and reimbursements that must be absorbed by the hospital. The GLMMIX is needed when the distribution of the data is not normal or may not have an exact distribution	proc step, proc mixed, proc genmod, proc glimmix, proc glm, sample, response variable	6
23	SAS And Unix: Techniques For Developing Your Toolbox	Joe Novotny	How many times have you had to write and run short SAS programs to determine the contents of a SAS data set or determine a simple frequency count of a variable? What if you could perform these tasks with a few simple keystrokes from the UNIX command line? Have you ever needed to create a SAS data set containing file information for numerous SAS files existing in a UNIX directory? This paper highlights several useful SAS features you should be aware of to take advantage of SAS's ability to interface with UNIX. The paper demonstrates practical applications of: 1) reading the UNIX command line into a SAS program, 2) printing SAS output to the UNIX terminal screen and 3) techniques that allow you to utilize UNIX information and execute UNIX commands from within SAS programs. These techniques can be used to automate many daily tasks, simplify more complex tasks and increase your overall programming productivity	dataset, proc step, macro definition, macro variable, proc printto, filename statement, sas output, automatic macro variable, call symput, proc contents, proc format, proc freq	7
24	SAS Enterprise Guide in Pharmaceutical Applications: Automated Analysis And Reporting	Alex Dmitrienko	SAS Enterprise Guide is a member of the SAS Business Intelligence suite, a broad collection of software products featuring intuitive point-and-click interfaces. Enterprise Guide offers an impressive selection of standard data manipu- lation and analysis tasks and provides a framework for developing new custom tasks. Due to an increasing demand to streamline routine data management and output generation tasks in the pharmaceutical world, Enterprise Guide will likely become one of the main tools for a broad group of pharmaceutical professionals involved in the so-called AAAA processes (data acquisition, aggregation, access and analysis), i.e., information technology, data management, statistics, etc. This paper describes how pharmaceutical companies can utilize Enterprise Guide to build systems for automating statistical analysis and reporting	sas enterprise guide, clinical trial, business intelligence, macro definition, data cleaning, character variable, proc freq, clinical data, dataset, proc means, data governance	9
25	SAS Enterprise Guide: Introduction To Stored Processes And Custom Tasks	Alex Dmitrienko	SAS Enterprise Guide provides a powerful framework for creating new tools known as stored processes and custom tasks. These tools are conceptually similar to SAS macros but, unlike regular macros, they feature attractive graphical user interfaces and can significantly shorten the user's learning curve and greatly increase his/her produc - tivity. This paper provides an overview of main features of stored processes and custom tasks and discusses development/ installation procedures. It also provides useful information for custom task developers, for example, describes the underlying data model, how custom tasks interact with the SAS System and how to build custom task using Microsoft Visual Basic or other languages	sas enterprise guide, macro definition, business intelligence, data cleaning, proc freq	7
26	SAS Excels!	Gerald D. Frey	This paper will introduce several techniques for supplying data from SAS to MS `EXCEL`. SAS can produce detailed, summarized, and categorized data or reports. Frequently; end users desire this information in an `EXCEL` spreadsheet. Fortunately, using SAS we can provide `EXCEL` information from various platforms using several different techniques: This paper will examine the following techniques: Export Wizard New SAS Explorer options in SAS 9 Custom `DATA STEP` SSCFLAT macro Windows ODBC connection New in SAS 9, MS `EXCEL` `LIBNAME` engine	excel, sas 9, dataset, proc step, xls, libname engine, odbc connection, output delivery system	9
27	Speedily Process Multiple Data Files Within SAS	Edgar Adams	Using knowledge of the windows file naming and folder structure to rapidly process multiple data files using SAS Macro code	macro definition, dataset	10
28	Spicing Up SAS/IntrNet Applications	Jonah P. Turner	With the advent of `SAS/INTRNET` software, SAS programmers can extend their applications online to cross-platform, global end-users. The paper "A Pinch of SAS , a Fraction of HTML, and a Touch of JavaScript Serve Up a Grand Recipe," published in the SUGI 28 proceedings, provided an introductory approach to developing programs that function via the Web. The next paper in this series, "A Recipe for Success: Migrating `SAS/AF` Applications to the Web Using SAS , HTML, and JavaScript," issued for SUGI 29, expounded on the subject by offering a workable method for modernizing legacy SAS windowing programs. Whereas these both outline basic strategies for implementing Web-based systems, this third installment goes a step further by demonstrating a variety of techniques suitable for spicing up such `SAS/INTRNET` applications. Programmers can add more flavor to th eir `SAS/INTRNET` applications using the same ingredients by way of enriching procedure output and enhancing interface functionality	macro definition, put statement, flag variable	15
29	Thirty Three Tricks With The Powerful Report Procedure	Ben Cochran	When the `REPORT` Procedure was first introduced by SAS with the advent of Version 6, most of the SAS world was mainframe users. This new procedure brought with it a great deal of power and flexibility that added much strength to SAS' arsenal of report generating procedures. It had powerful formatting, summarizing, and analysis capabilities that made it easier to create anything from a simple listing to a very complex report. However, some critics have stated that, while it has awesome features, it looks like a mainframe report. That was true until SAS released the Output Delivery System (`ODS`) experimentally in Version 7, and in production mode in Version 8. If the `REPORT` procedure was a cake, then `ODS` delivers the icing to generate truly beautiful reports. This paper offers a quick overview of the types of reports that can be generated with `PROC REPORT`, and how to add some of the `ODS` features to deliver stunning reports	proc report, proc step, output delivery system	12
30	Time Dependent Data Exploration And Preprocessing: Doing It All By SAS	Joseph Twagilimana	This paper presents exploration and preprocessing methodology of transactional data in order to transform the data into a multivariate time series and select an adequate model for analysis. Unlike time series data, where observations are equally spaced by a specific time interval, in transactional data, observations are not spaced with respect to any particular time period. Our approach is illustrated using observations of length of stay (LOS) of a patient at a hospital Emergency Department (ED). The challenges of analyzing these data include autocorrelations of the observations, non-linearity, and the fact that observations were not recoded at regular time intervals. First, using the SAS procedure, `PROC HPF`, we transformed the transactional data set into multivariate time series data	time series analysis, proc step, unit root, histogram, time series data, null hypothesis, covariance, outlier, lognormal distribution, normal distribution, correlation, confidence interval, data science, proc univariate, standard deviation, box plot, density plot	10
31	Twenty Two Tricks With The GPLOT And GCHART Procedures	Ben Cochran	The power and flexibility of `SAS/GRAPH` software enables the user to produce high quality graphs, charts, and maps. With all this strength and flexibility, th e new user is sometimes overwhelmed and discouraged from using these powerful tools. However, learning how to use the tools of `SAS/GRAPH` can be a pleasant experience. This paper introduces several ways to generate graphical representations of your data. Starting with the importance of understanding their data, users are lead in a step by step process that ends with the generation of high quality plots and graphs. Let us begin. Step 1: Understanding Your Data. Is some data more appropriate for generating graphical reports than other data? What data is most appropriate for plots and graphs? The first data set to be examined is the SASUSER.RETAIL table. A quick look at the first ten rows reveals only 2 columns or variables: SALES, and DATE. The SALES variable has a descriptive label associated with it. Both variables are numeric	proc gchart, proc step, bar chart, proc gplot	8
32	Use Proc Format To Apply Value Specific Suffixes To Your Data	Lara Guttadauro	If you need to apply value specific suffixes to your data, `PROC FORMAT` in SAS is a great option. You have the choice of using the picture option once or the value option twice	proc format, proc step	2
33	Using Macro Functions	Arthur L. Carpenter	Many macro functions are very analogous to those of the DATA st ep. The differences are in how they are used and applied. While `DATA STEP` functions are applied to values on the Program Data Vector, PDV, macro functions are used to create, modify, and work with text strings. Initially this may seem like a minor difference, but because macro functions deal with text, they can be used to build SAS code. This becomes the powerful advantage of the macro language. The use of various macro functions will be presented. Some of these functions return quoted results, and macro quoting functions will be introduced. Examples will include functi ons like %SYSEVALF and %SYSFUNC, which were new to V6.11 and V6.12, as well as, various Autocall macros. Several of the examples are adapted with the author's permission from "Carpenter's Complete Guide to the SAS Macro Language, Second Edition"	macro variable, macro function, macro facility, macro put, proc print, macro definition, character functions, macro call, proc step, macro quoting function, %if-%then-%else, autocall macro	10
34	Using Meta and Project Data for Data Driven Programming	Brian K. Varney	Creating dynamic, data driven programs is a very powerful tool. Often we can use the metadata or the project data itself to help write our programs. This paper will introduce some of the concepts related to writing SAS programs which will generate pieces of SAS code in a data driven manner. Parts of the SAS language used in this discussion include the following: 1. macro call routines (call execute, call symput)	macro variable, proc sql, proc step, call execute, dictionary tables, macro loop, data step, label statement	8
35	Using SAS For Spatial Analysis	Christina Pertrou	The aim of this paper is to identify major trends in several cardiac and respiratory conditions, and to analyze correlations such as median income and geographical locations for Jefferson County patients in Kentucky. This study dealt with geographical interpretation and statistical data manipulation. ArcGIS was used to compile, author, analyze, map, and publish geographic information and knowledge in combination with the statistical software package, SAS, using the SAS Bridge to ESRI developed jointly between the SAS Institute, Inc., and ESRI, Inc. This study used approximately 5000 patient records. Using ARC toolbox, the proximity of patient to the nearest provider was computed using the Near command. Conducting text mining in Enterprise Miner, the patients were clustered according to similarities of the word descriptions of the DRG codes, or Diagnosis Related Group, which refers to a system of describing and classifying the hospitals' patients	statistical software, data mining, correlation	5
36	Using SAS To Assess Dose Proportionality In Dose Escalation Studies	Keith Dunnigan	Dose escalation studies provide a good opportunity to assess the linearity of PK parameters. This paper describes hypothesis testing and confidence interval (C.I.) methods for assessing dose proportionality based on linear regression and weighted least squares (WLS) linear regression. SAS code is presented using an example study and AUCinf data	proc reg, confidence interval, regression analysis, pk parameter, simple linear regression, weighted least squares, sample, bootstrap, dose escalation, dose, anova	12
37	What's New And Upcoming In SAS 9 ODS	Tim Hunter		anova, output delivery system, estimate, excel, proc step, proc glm, proc freq	38
38	Where Proc Freq Ends And Proc Report Begins	Thushan Wijesinghe	The paper describes the applications of `PROC REPORT` in real business situations. In many cases we need to cleanse the data and then run it through a statistical procedure (`PROC RANK` is used in this case for segmentation purposes) before any reports can be prepared. The paper will detail how to create a dashboard type report using `PROC REPORT` with SAS `ODS`. The paper will start with the basics of the `REPORT` PROCEDURE such as how to create a report header and how to change the report's appearance (font size, color, etc). The final section of the paper will exhibit how to use some of advanced functions of the `REPORT` PROCEDURE such as the COMPUTE option, and using ANALYSIS, SUM and ACROSS variables with the DEFINE statement. In addition the paper will illustrate the use of the COMPUTE statement for traffic light ing (to color individuals cells within the report based on predefined criteria)	proc report, proc step, proc freq, proc rank	9

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