Power Calculations in Meta-Analysis
Zhaochong Yu
Co-Author
Division of Biostatistics and Bioinformatics, DEPHS, University of Cincinnati
Wednesday, Aug 7: 8:50 AM - 9:05 AM
3150
Contributed Papers
Oregon Convention Center
Power calculations in the environment of testing hypotheses are well hashed out. To unleash these calculations, we need 1. A family of models; 2. A null hypothesis; 3. The alternative hypothesis; 4. Data; 5. A test statistic T 6. The distribution of T under the null and alternative hypotheses; 7. Alpha; 9. A test. Power calculations let us choose a test and sample size. The main goal of this presentation is to bring entire modus operandi into the realm of Meta-Analysis. The overarching purpose of Meta-Analysis is to synthesize several studies all focusing on the same testing problem. Let m be the number of studies chosen for synthesis. Information on the studies is collected in two ways. 1. Relevant summary statistics from each study. 2. P-values from each study. There are studies, which give only p-values. These studies are the focus of this presentation. There are scores of tests proposed and used in the literature on synthesis. Tippett's test, Fisher's test, Pearson's test are some examples. We initiate power calculations as a function m of the number of studies on these tests. We show how power calculations help us to make comparisons between the tests.
Power
Sample Size
Meta-Analysis
Tippett test
Fisher test
Number of Studies for Meta-Analysis
Main Sponsor
Section on Statistical Computing
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