Journal
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
Volume 110, Issue 509, Pages 357-367Publisher
AMER STATISTICAL ASSOC
DOI: 10.1080/01621459.2014.903846
Keywords
Asymptotic properties; Clinical trial; Generalized linear models; Personalized medicine; Power; Randomization
Categories
Funding
- NSF [DMS-0906610, DMS-0907297, DMS-1209164, DMS-0706818, NIH R01 RGM080503A, NIH R01 CA158113]
- Cancer Center Support Grant [P30 CA016672]
- University of Texas School of Public Health starting up fund
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1442192] Funding Source: National Science Foundation
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Response-adaptive designs have recently attracted more and more attention in the literature because of its advantages in efficiency and medical ethics. To develop personalized medicine, covariate information plays an important role in both design and analysis of clinical trials. A challenge is how to incorporate covariate information in response-adaptive designs while considering issues of both efficiency and medical ethics. To address this problem, we propose a new and unified family of covariate-adjusted response-adaptive (CARA) designs based on two general measurements of efficiency and ethics. Important properties (including asymptotic properties) of the proposed procedures are studied under categorical covariates. This new family of designs not only introduces new desirable CARA designs, but also unifies several important designs in the literature. We demonstrate the proposed procedures through examples, simulations, and a discussion of related earlier work.
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