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Partition testing in confirmatory adaptive designs with structured objectives
Author(s) -
Sugitani Toshifumi,
Hamasaki Toshimitsu,
Hamada Chikuma
Publication year - 2013
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201200218
Subject(s) - bonferroni correction , partition (number theory) , computerized adaptive testing , computer science , sample size determination , machine learning , data mining , mathematics , statistics , psychometrics , combinatorics
In this paper, we propose a partition testing for adaptive clinical trials with structured study objectives. The proposed approach is a combination of the graphical approach with partition testing. The proposed approach enables one to handle many types of structured objectives, to tailor a multiple test procedure to given structured objectives, and to draw sensible conclusions in adaptive clinical trials. In addition, the proposed approach reduces to the Bonferroni‐based graphical approaches that can allow adaptations such as treatment selection and sample size reassessment during the course of the trial. Some practical aspects of the proposed approach are investigated via a simulation study.