Response-adaptive treatment allocation for clinical studies with ordinal responses
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AbstractOrdinal responses are common in clinical studies. Although the proportional odds model is a popular option for analyzing ordered-categorical data, it cannot control the type I error rate when the proportional odds assumption fails to hold. The latent Weibull model was recently shown to be a superior candidate for modeling ordinal data, with remarkably better performance than the latent normal model when the data are highly skewed. In clinical trials with ordinal responses, a balanced design is common, with equal sample allocation for each treatment. However, a more ethical approach is to adopt a response-adaptive allocation scheme in which more patients receive the better treatment. In this paper, we propose the use of the doubly adaptive biased coin design to generate treatment allocations that benefit the trial participants. The proposed treatment allocation scheme not only allows more patients to receive the better treatment, it also maintains compatible test power for the comparison of treatment efficiencies. A clinical example is used to illustrate the proposed procedure.
Acceptance Date07/03/2019
All Author(s) ListLu TY, Chung KP, Poon WY, Cheung SH
Journal nameStatistical Methods in Medical Research
Year2020
Month2
Volume Number29
Issue Number2
Pages359 - 373
ISSN0962-2802
eISSN1477-0334
LanguagesEnglish-United States
KeywordsAdaptive treatment allocation, ordered-categorical responses, doubly adaptive biased coin design, latent Weibull model, allocation function

Last updated on 2020-19-10 at 00:32