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Simple procedures for blinded sample size adjustment that do not affect the type I error rate
Author(s) -
Kieser Meinhard,
Friede Tim
Publication year - 2003
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.1585
Subject(s) - sample size determination , type i and type ii errors , estimator , statistics , variance (accounting) , mathematics , computer science , sample (material) , statistical power , econometrics , chemistry , accounting , chromatography , business
Abstract For normally distributed data, determination of the appropriate sample size requires a knowledge of the variance. Because of the uncertainty in the planning phase, two‐stage procedures are attractive where the variance is reestimated from a subsample and the sample size is adjusted if necessary. From a regulatory viewpoint, preserving blindness and maintaining the ability to calculate or control the type I error rate are essential. Recently, a number of proposals have been made for sample size adjustment procedures in the t‐test situation. Unfortunately, none of these methods satisfy both these requirements. We show through analytical computations that the type I error rate of the t‐test is not affected if simple blind variance estimators are used for sample size recalculation. Furthermore, the results for the expected power of the procedures demonstrate that the methods are effective in ensuring the desired power even under initial misspecification of the variance. A method is discussed that can be applied in a more general setting and that assumes analysis with a permutation test. This procedure maintains the significance level for any design situation and arbitrary blind sample size recalculation strategy. Copyright © 2003 John Wiley & Sons, Ltd.