Optimal Designs for Evaluating a Series of Treatments
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 subs...
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sg-smu-ink.soe_research-17622021-04-08T08:55:19Z Optimal Designs for Evaluating a Series of Treatments Leung, Denis H. Y. WANG, You Gan 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. 2001-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/763 info:doi/10.1111/j.0006-341X.2001.00168.x https://ink.library.smu.edu.sg/context/soe_research/article/1762/viewcontent/Optimal_designs_for_evaluating_a_series_of_treatments_av.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Bayesian Optimality Phase I studies Screening Sequential trials Soft tissue sarcoma Econometrics Medicine and Health Sciences |
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Bayesian Optimality Phase I studies Screening Sequential trials Soft tissue sarcoma Econometrics Medicine and Health Sciences Leung, Denis H. Y. WANG, You Gan Optimal Designs for Evaluating a Series of Treatments |
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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. |
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Leung, Denis H. Y. WANG, You Gan |
author_facet |
Leung, Denis H. Y. WANG, You Gan |
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Leung, Denis H. Y. |
title |
Optimal Designs for Evaluating a Series of Treatments |
title_short |
Optimal Designs for Evaluating a Series of Treatments |
title_full |
Optimal Designs for Evaluating a Series of Treatments |
title_fullStr |
Optimal Designs for Evaluating a Series of Treatments |
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Optimal Designs for Evaluating a Series of Treatments |
title_sort |
optimal designs for evaluating a series of treatments |
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Institutional Knowledge at Singapore Management University |
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2001 |
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https://ink.library.smu.edu.sg/soe_research/763 https://ink.library.smu.edu.sg/context/soe_research/article/1762/viewcontent/Optimal_designs_for_evaluating_a_series_of_treatments_av.pdf |
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