Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs

In clinical studies, multiple superiority/equivalence testing procedures can be applied to classify a new treatment as superior, equivalent (same therapeutic effect), or inferior to each set of standard treatments. Previous stepwise approaches (Dunnett and Tamhane, 1997, Statistics in Medicine 16, 2...

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Main Authors: KWONG, Koon Shing, CHEUNG, Siu Hung, CHAN, Wai-Sum
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Language:English
Published: Institutional Knowledge at Singapore Management University 2004
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Online Access:https://ink.library.smu.edu.sg/soe_research/35
https://ink.library.smu.edu.sg/context/soe_research/article/1034/viewcontent/Kwong_et_al_2004_MultipleTesting.pdf
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spelling sg-smu-ink.soe_research-10342018-05-04T06:47:49Z Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs KWONG, Koon Shing CHEUNG, Siu Hung CHAN, Wai-Sum In clinical studies, multiple superiority/equivalence testing procedures can be applied to classify a new treatment as superior, equivalent (same therapeutic effect), or inferior to each set of standard treatments. Previous stepwise approaches (Dunnett and Tamhane, 1997, Statistics in Medicine 16, 2489–2506; Kwong, 2001, Journal of Statistical Planning and Inference 97, 359–366) are only appropriate for balanced designs. Unfortunately, the construction of similar tests for unbalanced designs is far more complex, with two major difficulties: (i) the ordering of test statistics for superiority may not be the same as the ordering of test statistics for equivalence; and (ii) the correlation structure of the test statistics is not equi-correlated but product-correlated. In this article, we seek to develop a two-stage testing procedure for unbalanced designs, which are very popular in clinical experiments. This procedure is a combination of step-up and single-step testing procedures, while the familywise error rate is proved to be controlled at a designated level. Furthermore, a simulation study is conducted to compare the average powers of the proposed procedure to those of the single-step procedure. In addition, a clinical example is provided to illustrate the application of the new procedure. 2004-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/35 info:doi/10.1111/j.0006-341X.2004.00194.x https://ink.library.smu.edu.sg/context/soe_research/article/1034/viewcontent/Kwong_et_al_2004_MultipleTesting.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Coherence property Equivalent efficacy Familywise error rate Multivariate t-distribution Econometrics Medicine and Health Sciences
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Coherence property
Equivalent efficacy
Familywise error rate
Multivariate t-distribution
Econometrics
Medicine and Health Sciences
spellingShingle Coherence property
Equivalent efficacy
Familywise error rate
Multivariate t-distribution
Econometrics
Medicine and Health Sciences
KWONG, Koon Shing
CHEUNG, Siu Hung
CHAN, Wai-Sum
Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs
description In clinical studies, multiple superiority/equivalence testing procedures can be applied to classify a new treatment as superior, equivalent (same therapeutic effect), or inferior to each set of standard treatments. Previous stepwise approaches (Dunnett and Tamhane, 1997, Statistics in Medicine 16, 2489–2506; Kwong, 2001, Journal of Statistical Planning and Inference 97, 359–366) are only appropriate for balanced designs. Unfortunately, the construction of similar tests for unbalanced designs is far more complex, with two major difficulties: (i) the ordering of test statistics for superiority may not be the same as the ordering of test statistics for equivalence; and (ii) the correlation structure of the test statistics is not equi-correlated but product-correlated. In this article, we seek to develop a two-stage testing procedure for unbalanced designs, which are very popular in clinical experiments. This procedure is a combination of step-up and single-step testing procedures, while the familywise error rate is proved to be controlled at a designated level. Furthermore, a simulation study is conducted to compare the average powers of the proposed procedure to those of the single-step procedure. In addition, a clinical example is provided to illustrate the application of the new procedure.
format text
author KWONG, Koon Shing
CHEUNG, Siu Hung
CHAN, Wai-Sum
author_facet KWONG, Koon Shing
CHEUNG, Siu Hung
CHAN, Wai-Sum
author_sort KWONG, Koon Shing
title Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs
title_short Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs
title_full Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs
title_fullStr Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs
title_full_unstemmed Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs
title_sort multiple testing to establish superiority/equivalence of a new treatment compared with k standard treatments for unbalanced designs
publisher Institutional Knowledge at Singapore Management University
publishDate 2004
url https://ink.library.smu.edu.sg/soe_research/35
https://ink.library.smu.edu.sg/context/soe_research/article/1034/viewcontent/Kwong_et_al_2004_MultipleTesting.pdf
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