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Performance of adaptive sample size adjustment with respect to stopping criteria and time of interim analysis
Author(s) -
JahnEimermacher Antje,
Hommel Gerhard
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.2652
Subject(s) - interim , interim analysis , early stopping , sample size determination , sample (material) , computer science , econometrics , statistics , clinical trial , mathematics , medicine , artificial intelligence , chemistry , archaeology , pathology , chromatography , artificial neural network , history
Abstract The benefit of adjusting the sample size in clinical trials on the basis of treatment effects observed in interim analysis has been the subject of several recent papers. Different conclusions were drawn about the usefulness of this approach for gaining power or saving sample size, because of differences in trial design and setting. We examined the benefit of sample size adjustment in relation to trial design parameters such as ‘time of interim analysis’ and ‘choice of stopping criteria’. We compared the adaptive weighted inverse normal method with classical group sequential methods for the most common and for optimal stopping criteria in early, half‐time and late interim analyses. We found that reacting to interim data might significantly reduce average sample size in some situations, while classical approaches can out‐perform the adaptive designs under other circumstances. We characterized these situations with respect to time of interim analysis and choice of stopping criteria. Copyright © 2006 John Wiley & Sons, Ltd.