Response-adaptive treatment allocation for clinical studies with ordinal responses
Publication in refereed journal

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摘要Ordinal 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.
出版社接受日期07.03.2019
著者Lu TY, Chung KP, Poon WY, Cheung SH
期刊名稱Statistical Methods in Medical Research
出版年份2020
月份2
卷號29
期次2
頁次359 - 373
國際標準期刊號0962-2802
電子國際標準期刊號1477-0334
語言美式英語
關鍵詞Adaptive treatment allocation, ordered-categorical responses, doubly adaptive biased coin design, latent Weibull model, allocation function

上次更新時間 2020-21-11 於 23:46