Power analyses for longitudinal trials and other clustered designs

Xin M. Tu, J. Kowalski, J. Zhang, K. G. Lynch, P. Crits-Christoph

Research output: Contribution to journalReview articlepeer-review

33 Scopus citations


Existing methods for power and sample size estimation for longitudinal and other clustered study designs have limited applications. In this paper, we review and extend existing approaches to improve these limitations. In particular, we focus on power analysis for the two most popular approaches for clustered data analysis, the generalized estimating equations and the linear mixed-effects models. By basing the derivation of the power function on the asymptotic distribution of the model estimates, the proposed approach provides estimates of power that are consistent with the methods of inference for data analysis. The proposed methodology is illustrated with numerous examples that are motivated by real study designs.

Original languageEnglish (US)
Pages (from-to)2799-2815
Number of pages17
JournalStatistics in Medicine
Issue number18
StatePublished - Sep 30 2004


  • Epidemiological study
  • GEE
  • HIV
  • Intraclass correlation
  • Linear mixed-effects models
  • Psychosocial and survey research

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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