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Power and sample size computations in simultaneous tests for non‐inferiority based on relative margins
Author(s) -
Dilba Gemechis,
Bretz Frank,
Hothorn Ludwig A.,
Guiard Volker
Publication year - 2006
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.2359
Subject(s) - sample size determination , inference , margin (machine learning) , statistics , computation , sample (material) , mathematics , statistical power , power (physics) , multiple comparisons problem , computer science , econometrics , algorithm , artificial intelligence , machine learning , chemistry , physics , chromatography , quantum mechanics
Abstract In this paper, we address the problem of calculating power and sample sizes associated with simultaneous tests for non‐inferiority. We consider the case of comparing several experimental treatments with an active control. The approach is based on the ratio view, where the common non‐inferiority margin is chosen to be some percentage of the mean of the control treatment. Two power definitions in multiple hypothesis testing, namely, complete power and minimal power, are used in the computations. The sample sizes associated with the ratio‐based inference are also compared with that of a comparable inference based on the difference of means for various scenarios. It is found that the sample size required for ratio‐based inferences is smaller than that of difference‐based inferences when the relative non‐inferiority margin is less than one and when large response values indicate better treatment effects. The results are illustrated with examples. Copyright © 2005 John Wiley & Sons, Ltd.