title: Decision rule based multiplicity adjustment strategy.
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.
authors.affiliation: Clinical Biostatistics, Sanofi-Aventis, Bridgewater, NJ 08807, USA. xun.chen@sanofi-aventis.com
authors.forename: Xun
authors.initials: X
authors.lastname: Chen
authors.forename: Tom
authors.initials: T
authors.lastname: Capizzi
authors.forename: Bruce
authors.initials: B
authors.lastname: Binkowitz
authors.forename: Hui
authors.initials: H
authors.lastname: Quan
authors.forename: Lynn
authors.initials: L
authors.lastname: Wei
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Luo
mesh_terms: D050071:Bone Density Conservation Agents / Q000627:therapeutic use; D002986:Clinical Trials as Topic; D003627:Data Interpretation, Statistical; D003661:Decision Support Techniques; D006801:Humans; D010024:Osteoporosis / Q000188:drug therapy; D020849:Raloxifene Hydrochloride / Q000627:therapeutic use
chemical_list: D050071:Bone Density Conservation Agents; D020849:Raloxifene Hydrochloride