From sasCommunity

Chair: Jennifer Waller and Tyler Smith

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SAS Analytics has been and will continue to be a pillar in the statistical community. Increased visibility of integrated analytic tool sets has lead to application in a vast range of business, healthcare, and other challenges. The Statistics and Data Analysis section offers an opportunity to see analytic methods with accompanying SAS programming from statisticians, economists, epidemiologists, forecasters, and operations and market researchers. Presenting in this forum will advance, educate and shape the application of statistical methods in a multidisciplinary setting. Whether you have special insight or data use for one of the many known SAS statistical procedures in SAS/STAT®, SAS/QC® and SAS/ETS®, or you are on the cutting edge of statistical evolution and its implementation with SAS and JMP® products, your contribution will be welcome. Of special interest this year are papers on:

• Application of analytical methods to solve real data encounters with special emphasis in survival analytic techniques.
• New analytical techniques available in SAS 9.2 such as Bayesian analysis with PROC MCMC
• Statistical methods for clinical trials and cross-over designs with PROC TTEST, SEQDESIGN, and SEQTEST.

SAS Global Forum 2010 Paper Topics Submissions

• To post an idea for a paper, click: Here is my idea

Your posting will be listed on this page.

• To add your comments to an existing idea, click on the Edit link beside the topic

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The following subsections list previously suggested topics:

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Interface to R

Announced at SAS Global Forum 2009 was the capability to link between SAS and R. Given that many state of the art techniques are only available in R, this is an exciting concept to those who are regular SAS users and have their data stored in SAS. A paper about this would probably be quite useful.

Useful macros for statistical analysis

In the macro section, most papers are about macros to do things that are part of the data step. But there are lots of useful ways to use macros in statistical analysis. Most of these are fairly simple, but many people who use mostly (or only) SAS/STAT may not be aware of them. Even simply using macro variables can save a lot of time, but simple things like

%macro kwtest(iv); ods exclude WilcoxonTest; proc npar1way data = champ wilcoxon;

class &iv;
var &dv;

run; %mend kwtest;

can be very helpful when doing exploratory analysis.