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  • Jaki_et_al-2016-Pharmaceutical_Statistics

    Rights statement: ©2016 The Authors. Pharmaceutical Statistics Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Why are two mistakes not worse than one?: a proposal for controlling the expected number of false claims

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published
<mark>Journal publication date</mark>07/2016
<mark>Journal</mark>Pharmaceutical Statistics
Issue number4
Volume15
Number of pages6
Pages (from-to)362-367
Publication StatusPublished
Early online date20/04/16
<mark>Original language</mark>English

Abstract

Multiplicity is common in clinical studies and the current standard is to use the familywise error rate to ensure that the errors are kept at a prespecified level. In this paper, we will show that, in certain situations, familywise error rate control does not account for all errors made. To counteract this problem, we propose the use of the expected number of false claims (EFC). We will show that a (weighted) Bonferroni approach can be used to control the EFC, discuss how a study that uses the EFC can be powered for co-primary, exchangeable, and hierarchical endpoints, and show how the weight for the weighted Bonferroni test can be determined in this manner.

Bibliographic note

©2016 The Authors. Pharmaceutical Statistics Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.