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

Author

Listed:
  • Evridiki Batistatou

    (Centre for Epidemiology, University of Manchester)

  • Chris Roberts

    (Centre for Biostatistics, University of Manchester)

  • Steve Roberts

    (Centre for Biostatistics, University of Manchester)

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.

Suggested Citation

  • Evridiki Batistatou & Chris Roberts & Steve Roberts, 2014. "Sample size and power calculations for trials and quasi-experimental studies with clustering," Stata Journal, StataCorp LP, vol. 14(1), pages 159-175, March.
    • Handle: RePEc:tsj:stataj:v:14:y:2014:i:1:p:159-175
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    Cited by:

    1. Matteo Migheli & Margherita Saraceno, 2023. "On the propensity to settle or litigate in laboratory disputes," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 40(2), pages 615-642, July.

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