Asymptotic Properties of Covariate-Adjusted Adaptive Designs

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dc.creatorZhang, Li-Xin
dc.creatorHu, Feifang
dc.creatorCheung, Siu Hung
dc.creatorChan, Wai Sum
dc.date2006-10-17
dc.date.accessioned2026-07-07T12:22:04Z
dc.date.available2026-07-07T12:22:04Z
dc.descriptionResponse-adaptive designs have been extensively studied and used in clinical trials. However, there is a lack of a comprehensive study of response-adaptive designs that include covariates, despite their importance in clinical experiments. Because the allocation scheme and the estimation of parameters are affected by both the responses and the covariates, covariate-adjusted response-adaptive (CARA) designs are very complex to formulate. In this paper, we overcome the technical hurdles and lay out a framework for general CARA designs for the allocation of subjects to $K (\geq 2)$ treatments. The asymptotic properties are studied under certain widely satisfied conditions. The proposed CARA designs can be applied to generalized linear models. Two important special cases, the linear model and the logistic regression model, are considered in detail.
dc.identifierhttps://arxiv.org/abs/math/0610518
dc.identifierhttp://arxiv.org/abs/math/0610518
dc.identifierThe Annals of Statistics, Vol. 35(2007):1166-1182
dc.identifierdoi:10.1214/009053606000001424
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/213531
dc.subjectStatistics Theory
dc.subjectProbability
dc.subjectMethodology
dc.subject60F15; 62G10; 60G10; 60F05
dc.titleAsymptotic Properties of Covariate-Adjusted Adaptive Designs
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