Sequential estimation for covariate-adjusted response-adaptive designs
نویسندگان
چکیده
منابع مشابه
Asymptotic Properties of Covariate - Adjusted Response - Adaptive Designs
Response-adaptive designs have been extensively studied and used in clinical trials. However, there is a lack of a comprehensive study of responseadaptive designs that include covariates, despite their importance in clinical trials. Because the allocation scheme and the estimation of parameters are affected by both the responses and the covariates, covariate-adjusted responseadaptive (CARA) des...
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Owing to the benefits that higher proportions of patients are likely to receive the better treatment, response-adaptive designs are considered to be valuable statistical tools in clinical studies. Nevertheless, there is a lack of a comprehensive study of adaptive designs with the inclusion of covariates, regardless of their importance in clinical experiments. The major reason is that covariatea...
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We propose a new estimation procedure for covariate adjusted nonlinear regression models for situations where both the predictors and response in a nonlinear regression model are not directly observed, however distorted versions of the predictors and response are observed. The distorted versions are assumed to be contaminated with a multiplicative factor that is determined by the value of an un...
متن کاملStart-up designs for response-adaptive randomization procedures with sequential estimation.
Response-adaptive randomization procedures are appropriate for clinical trials in which two or more treatments are to be compared, patients arrive sequentially and the response of each patient is recorded before the next patient arrives. However, for those procedures that involve sequential estimation of model parameters, start-up designs are commonly required in order to provide initial estima...
متن کاملCovariate - Adjusted Nonlinear Regression
In this paper, we propose a covariate-adjusted nonlinear regression model. In this model, both the response and predictors can only be observed after being distorted by some multiplicative factors. Because of nonlinearity, existing methods for the linear setting cannot be directly employed. To attack this problem, we propose estimating the distorting functions by nonparametrically regressing th...
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ژورنال
عنوان ژورنال: Journal of the Korean Statistical Society
سال: 2013
ISSN: 1226-3192
DOI: 10.1016/j.jkss.2012.06.001