Publication Type
Journal Article
Version
acceptedVersion
Publication Date
3-2001
Abstract
Several articles in this journal have studied optimal designs for testing a series of treatments to identify promising ones for further study. These designs formulate testing as an ongoing process until a promising treatment is identified. This formulation is considered to be more realistic but substantially increases the computational complexity. In this article, we show that these new designs, which control the error rates for a series of treatments, can be reformulated as conventional designs that control the error rates for each individual treatment. This reformulation leads to a more meaningful interpretation of the error rates and hence easier specification of the error rates in practice. The reformulation also allows us to use conventional designs from published tables or standard computer programs to design trials for a series of treatments. We illustrate these using a study in soft tissue sarcoma.
Keywords
Bayesian, Optimality, Phase I studies, Screening, Sequential trials, Soft tissue sarcoma
Discipline
Econometrics | Medicine and Health Sciences
Research Areas
Econometrics
Publication
Biometrics
Volume
57
Issue
1
First Page
168
Last Page
171
ISSN
1541-0420
Identifier
10.1111/j.0006-341X.2001.00168.x
Publisher
Wiley
Citation
Leung, Denis H. Y. and WANG, You Gan.
Optimal Designs for Evaluating a Series of Treatments. (2001). Biometrics. 57, (1), 168-171.
Available at: https://ink.library.smu.edu.sg/soe_research/763
Copyright Owner and License
Authors
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.2001.00168.x