Sample size and power calculations in repeated measurement analysis

• Published in: Computer methods and programs in biomedicine 2001-02, Vol.64 (2), p.121-124
• Main Authors: Ahn, Chul, Overall, John E, Tonidandel, Scott
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Computer simulation; Computerized, statistical medical data processing and models in biomedicine; Controlled Clinical Trials as Topic - statistics & numerical data; Dropouts; Humans; Medical sciences; Medical statistics; Numerical analysis; Power calculation; Repeated measures; Sample Size; Sample size estimate; Schizophrenia - drug therapy; Software
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/S0169-2607(00)00095-X

Controlled clinical trials in neuropsychopharmacology, as in numerous other clinical research domains, tend to employ a conventional parallel-groups design with repeated measurements. The hypothesis of primary interest in the relatively short-term, double-blind trials, concerns the difference between patterns or magnitudes of change from baseline. A simple two-stage approach to the analysis of such data involves calculation of an index or coefficient of change in stage 1 and testing the significance of difference between group means on the derived measure of change in stage 2. This article has the aim of introducing formulas and a computer program for sample size and/or power calculations for such two-stage analyses involving each of three definitions of change, with or without baseline scores entered as a covariate, in the presence of homogeneous or heterogeneous (autoregressive) patterns of correlation among the repeated measurements. Empirical adjustments of sample size for the projected dropout rates are also provided in the computer program.