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Sample size requirement for repeated measurements in continuous data
Author(s) -
Lui KungJong,
Cumberland William G.
Publication year - 1992
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780110508
Subject(s) - sample size determination , repeated measures design , statistics , sample (material) , mathematics , variance (accounting) , analysis of variance , power (physics) , statistical power , computer science , accounting , chromatography , quantum mechanics , business , chemistry , physics
In this paper we extend Bloch's discussion on the usefulness and the limitations in the application of repeated measurements per subject in study designs. We derive general sample size formulae for any finite number of comparison groups to calculate the required number of subjects with repeated measurements, that do not have to be conditionally independent. For fixed total cost, we discuss the optimal sample allocation for repeated measurements needed to maximize the power and the underestimation when using Bloch's sample size formula if in the hypothesis testing procedure the variance parameters are unknown. We have also included a quantitative investigation of the effectiveness of taking repeated measurements per subject to reduced the required number of subjects for a given power at a given α‐level.