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Research article summary (published 27 Feb 2001):

Optimal designs for evaluating a series of treatments.

Full 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.

 

Author information

Author/s: Leung, D H (DH); Wang, Y G (YG);

Affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA. leung(-atsign-)biost.mskcc.org

Grants: AI24643 (Agency:NIAID NIH HHS) ; CA47179 (Agency:NCI NIH HHS) ; CA74207 (Agency:NCI NIH HHS)

Journal and publication information

Publication Type: Journal Article; Research Support, U.S. Gov't, P.H.S.

Journal: Biometrics (Biometrics), published in United States. (Language: eng)

Reference: 2001-Mar; vol 57 (issue 1) : pp 168-71

Dates: Created 2001/03/16; Completed 2001/06/28; Revised 2007/11/15;

PMID: 11252593, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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