Sample size determination for hierarchical longitudinal designs with differential attrition rates

Anindya Roy, Dulal K. Bhaumik, Subhash Aryal, Robert D. Gibbons

Research output: Contribution to journalArticle

50 Scopus citations

Abstract

We consider the problem of sample size determination for three-level mixed-effects linear regression models for the analysis of clustered longitudinal data. Three-level designs are used in many areas, but in particular, multicenter randomized longitudinal clinical trials in medical or health-related research. In this case, level 1 represents measurement occasion, level 2 represents subject, and level 3 represents center. The model we consider involves random effects of the time trends at both the subject level and the center level. In the most common case, we have two random effects (constant and a single trend), at both subject and center levels. The approach presented here is general with respect to sampling proportions, number of groups, and attrition rates over time. In addition, we also develop a cost model, as an aid in selecting the most parsimonious of several possible competing models (i.e., different combinations of centers, subjects within centers, and measurement occasions). We derive sample size requirements (i.e., power characteristics) for a test of treatment-by-time interaction(s) for designs based on either subject-level or cluster-level randomization. The general methodology is illustrated using two characteristic examples.

Original languageEnglish
Pages (from-to)699-707
Number of pages9
JournalBiometrics
Volume63
Issue number3
DOIs
StatePublished - 1 Sep 2007

Keywords

  • Cost analysis
  • Dropouts
  • Mixed effects
  • Power analysis
  • Profile analysis
  • Three-level nested design

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