Sample size determination in step-up testing procedures for multiple comparisons with a control

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 de...

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Main Authors: KWONG, Koon Shing, CHUENG, Siu Hung, WEN, Miin‐Jye
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Language:English
Published: Institutional Knowledge at Singapore Management University 2010
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Online Access:https://ink.library.smu.edu.sg/soe_research/1272
https://doi.org/10.1002/sim.4045
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spelling sg-smu-ink.soe_research-22712018-05-17T07:41:34Z Sample size determination in step-up testing procedures for multiple comparisons with a control KWONG, Koon Shing CHUENG, Siu Hung WEN, Miin‐Jye 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. 2010-11-01T07:00:00Z text https://ink.library.smu.edu.sg/soe_research/1272 info:doi/10.1002/sim.4045 https://doi.org/10.1002/sim.4045 Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University multiple comparisons with a control power function step-up test familywise error rate Econometrics Health Economics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic multiple comparisons with a control
power function
step-up test
familywise error rate
Econometrics
Health Economics
spellingShingle multiple comparisons with a control
power function
step-up test
familywise error rate
Econometrics
Health Economics
KWONG, Koon Shing
CHUENG, Siu Hung
WEN, Miin‐Jye
Sample size determination in step-up testing procedures for multiple comparisons with a control
description 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.
format text
author KWONG, Koon Shing
CHUENG, Siu Hung
WEN, Miin‐Jye
author_facet KWONG, Koon Shing
CHUENG, Siu Hung
WEN, Miin‐Jye
author_sort KWONG, Koon Shing
title Sample size determination in step-up testing procedures for multiple comparisons with a control
title_short Sample size determination in step-up testing procedures for multiple comparisons with a control
title_full Sample size determination in step-up testing procedures for multiple comparisons with a control
title_fullStr Sample size determination in step-up testing procedures for multiple comparisons with a control
title_full_unstemmed Sample size determination in step-up testing procedures for multiple comparisons with a control
title_sort sample size determination in step-up testing procedures for multiple comparisons with a control
publisher Institutional Knowledge at Singapore Management University
publishDate 2010
url https://ink.library.smu.edu.sg/soe_research/1272
https://doi.org/10.1002/sim.4045
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