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Multiple comparisons with a control in families with both one‐sided and two‐sided hypotheses
Author(s) -
Cheung Siu Hung,
Kwong Koon Shing,
Chan Wai Sum,
Leung Shun Piu
Publication year - 2004
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.1883
Subject(s) - computer science , control (management) , sample (material) , sample size determination , multiple comparisons problem , data mining , statistics , artificial intelligence , mathematics , chemistry , chromatography
Comparing several treatments with a control is a common objective of clinical studies. However, existing procedures mainly deal with particular families of inferences in which all hypotheses are either one‐ or two‐sided. In this article, we seek to develop a procedure which copes with a more general testing environment in which the family of inferences is composed of a mixture of one‐ and two‐sided hypotheses. The proposed procedure provides a more flexible and powerful tool than the existing method. The superiority of this method is also substantiated by a simulation study of average power. Selected critical values are tabulated for the implementation of the proposed procedure. Finally, we provide an illustrative example with sample data extracted from a medical experiment. Copyright © 2004 John Wiley & Sons, Ltd.