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Interim Analysis and Sample Size Reassessment
Author(s) -
Posch Martin,
Bauer Peter
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.01170.x
Subject(s) - sample size determination , null hypothesis , a priori and a posteriori , statistics , early stopping , mathematics , disjoint sets , interim , sample (material) , econometrics , alternative hypothesis , multiple comparisons problem , computer science , artificial intelligence , combinatorics , physics , philosophy , archaeology , epistemology , artificial neural network , history , thermodynamics
Summary. This article deals with sample size reassessment for adaptive two‐stage designs based on conditional power arguments utilizing the variability observed at the first stage. Fisher's product test for the p ‐values from the disjoint samples at the two stages is considered in detail for the comparison of the means of two normal populations. We show that stopping rules allowing for the early acceptance of the null hypothesis that are optimal with respect to the average sample size may lead to a severe decrease of the overall power if the sample size is a priori underestimated. This problem can be overcome by choosing designs with low probabilities of early acceptance or by midtrial adaptations of the early acceptance boundary using the variability observed in the first stage. This modified procedure is negligibly anticonservative and preserves the power.