Sample size determination in step-up testing procedures for multiple comparisons with a control
Publication Type
Journal Article
Publication Date
11-2010
Abstract
Step-up procedures have been shown to be powerful testing methods in clinical trials for comparisons of several treatments with a control. In this paper, a determination of the optimal sample size for a step-up procedure that allows a pre-specified power level to be attained is discussed. Various definitions of power, such as all-pairs power, any-pair power, per-pair power and average power, in one- and two-sided tests are considered. An extensive numerical study confirms that square root allocation of sample size among treatments provides a better approximation of the optimal sample size relative to equal allocation. Based on square root allocation, tables are constructed, and users can conveniently obtain the approximate required sample size for the selected configurations of parameters and power. For clinical studies with difficulties in recruiting patients or when additional subjects lead to a significant increase in cost, a more precise computation of the required sample size is recommended. In such circumstances, our proposed procedure may be adopted to obtain the optimal sample size. It is also found that, contrary to conventional belief, the optimal allocation may considerably reduce the total sample size requirement in certain cases. The determination of the required sample sizes using both allocation rules are illustrated with two examples in clinical studies.
Keywords
multiple comparisons with a control, power function, step-up test, familywise error rate
Discipline
Econometrics | Health Economics
Research Areas
Econometrics
Publication
Statistics in Medicine
Volume
29
Issue
26
First Page
2743
Last Page
2756
ISSN
0277-6715
Identifier
10.1002/sim.4045
Publisher
Wiley
Citation
KWONG, Koon Shing; CHUENG, Siu Hung; and WEN, Miin‐Jye.
Sample size determination in step-up testing procedures for multiple comparisons with a control. (2010). Statistics in Medicine. 29, (26), 2743-2756.
Available at: https://ink.library.smu.edu.sg/soe_research/1272
Additional URL
https://doi.org/10.1002/sim.4045