Sample size and power calculations for trials and quasi-experimental studies with clustering

Evridiki Batistatou (), Chris Roberts () and Steve Roberts ()
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Evridiki Batistatou: Centre for Epidemiology, University of Manchester
Chris Roberts: Centre for Biostatistics, University of Manchester
Steve Roberts: Centre for Biostatistics, University of Manchester

Stata Journal, 2014, vol. 14, issue 1, 159-175

Abstract: This article considers the estimation of power and sample size in experimental and quasi-experimental intervention studies, where there is clustering of subjects within one or both intervention arms, for both continuous and binary outcomes. A new command, clsampsi, which has a wide range of options, calculates the power and sample size needed (that is, the number of clusters and cluster size) by using the noncentral F distribution as described by Moser, Stevens, and Watts (1989, Communications in Statistics—Theory and Methods 18: 3963–3975). For comparative purposes, this command can also produce power and sample-size estimates on the basis of existing methods that use a normal approximation. Copyright 2014 by StataCorp LP.

Keywords: clsampsi; sample size; power calculation; intervention studies (search for similar items in EconPapers)
Date: 2014
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