Who Has the Power? Proc Power Kelly Guyton SAS Final Presentation

Introduction Determining power, type I error rate, and sample size are imperative to designing a successful epidemiologic study or clinical trial. Calculations are often complex and scientists must purchase expensive software.

Proc Power 1.Were added to Analyst window for SAS V SAS V9.1 introduced Proc power and Proc GLMpower as an experimental component. 3.Proc Power is full featured, easy to use, and tables can be added directly into other documents.

Statistical Tests Continuous methods: T-tests (1 and 2 sample, paired) ANOVA (repeated measure, and 2-way) Linear regression (simple, multiple) Wilcoxon (sign-rank, Man-Whitney) Equivalence Tests Confidence intervals

Statistical Tests Categorical Methods: BinomialChi-square Likelyhood ratio Fisher’s exact Mc Nemar’s Chochran Survival Tests: Log Rank Gehan Rank test

SAS Code-Means Sample Size Proc Power; Twosamplemeans meandiff=50 to 100 by 10 stddev=15 to 30 by 5 Groupweights=(1,3) power=0.8 ntotal=.; Plot y=power min=0.5 max=0.99; run;

SAS Code-Frequency Sample Size Proc Power; Twosamplefreq test=pchi proportiondiff=0.10 to 0.80 by 0.1 refproportion=0.26 power=0.9 alpha=0.05 to 0.25 by 0.05 ntotal=.; run;

SAS Code-Frequency Power calculation Proc Power; Twosamplefreq test=fisher proportiondiff=0.10 to 0.80 by 0.1 refproportion=0.26 npergroup=250 power=.; run;

Who Knew? SAS Genetics Proc Allele Proc Casecontrol Proc Family