Sample size estimation for GEE method for comparing slopes in repeated measurements data

Sin Ho Jung, Chul Ahn

Research output: Contribution to journalReview article

71 Scopus citations

Abstract

Sample size calculation is an important component at the design stage of clinical trials. Controlled clinical trials often use a repeated measurement design in which individuals are randomly assigned to treatment groups and followed-up for measurements at intervals across a treatment period of fixed duration. In studies with repeated measurements, one of the popular primary interests is the comparison of the rates of change in a response variable between groups. Statistical models for calculating sample sizes for repeated measurement designs often fail to take into account the impact of missing data correctly. In this paper we propose to use the generalized estimating equation (GEE) method in comparing the rates of change in repeated measurements and introduce closed form formulae for sample size and power that can be calculated, using a scientific calculator. Since the sample size formula is based on asymptotic theory, we investigate the performance of the estimated sample size in practical settings through simulations.

Original languageEnglish (US)
Pages (from-to)1305-1315
Number of pages11
JournalStatistics in Medicine
Volume22
Issue number8
DOIs
StatePublished - Apr 30 2003

Keywords

  • AR(1)
  • Compound symmetry
  • Independent missing
  • Independent working correlation
  • Missing completely at random
  • Monotone missing

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Fingerprint Dive into the research topics of 'Sample size estimation for GEE method for comparing slopes in repeated measurements data'. Together they form a unique fingerprint.

Cite this