K-sample test and sample size calculation for comparing slopes in data with repeated measurements

Sin Ho Jung, Chul Ahn

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Sample size calculations based on two-sample comparisons of slopes in repeated measurements have been reported by many investigators. In contrast, the literature has paid relatively little attention to the design and analysis of K-sample trials in repeated measurements studies where K is 3 or greater. Jung and Ahn (2003) derived a closed sample size formula for two-sample comparisons of slopes by taking into account the impact of missing data. We extend their method to compare K-sample slopes in repeated measurement studies using the generalized estimating equation (GEE) approach based on independent working correlation structure. We investigate the performance of the sample size formula since the sample size formula is based on asymptotic theory. The proposed sample size formula is illustrated using a clinical trial example.

Original languageEnglish (US)
Pages (from-to)554-564
Number of pages11
JournalBiometrical Journal
Volume46
Issue number5
DOIs
StatePublished - Sep 1 2004

Keywords

  • AR(1)
  • Compound symmetry
  • GEE estimator
  • Independent missing
  • Independent working correlation
  • Monotone missing

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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