Publication Type
Journal Article
Version
acceptedVersion
Publication Date
6-2004
Abstract
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.
Keywords
Coherence property, Equivalent efficacy, Familywise error rate, Multivariate t-distribution
Discipline
Econometrics | Medicine and Health Sciences
Research Areas
Econometrics
Publication
Biometrics
Volume
60
Issue
2
First Page
491
Last Page
498
ISSN
0006-341X
Identifier
10.1111/j.0006-341X.2004.00194.x
Publisher
Wiley
Citation
KWONG, Koon Shing; CHEUNG, Siu Hung; and CHAN, Wai-Sum.
Multiple Testing to Establish Superiority/Equivalence of a New Treatment Compared with K Standard Treatments for Unbalanced Designs. (2004). Biometrics. 60, (2), 491-498.
Available at: https://ink.library.smu.edu.sg/soe_research/35
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1111/j.0006-341X.2004.00194.x