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Decision rule based multiplicity adjustment strategy
Xun Chen1, Tom Capizzi, Bruce Binkowitz
1Clinical Biostatistics, Sanofi-Aventis, Bridgewater, NJ 08807, USA. xun.chen@sanofi-aventis.com
Abstract:
To minimize potential controversies in determining the need for multiplicity adjustment for multiple hypotheses, we propose a decision rule based multiplicity adjustment strategy in this paper. Resorting to a predefined decision rule of a clinical trial, one may link the different hypotheses by their logical relationships and divide them into different families. A proper multiplicity adjustment procedure can then be developed by maintaining strong control of Type I error rate within each family. The paper applies the proposed multiplicity adjustment strategy to a published raloxifene clinical trial.
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