Asymptotic properties of covariate-adjusted response-adaptive designs
نویسندگان
چکیده
منابع مشابه
Asymptotic Properties of Covariate - Adjusted Adaptive Designs
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...
متن کاملAsymptotic 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...
متن کاملAsymptotic Properties of Adaptive Designs via Strong Approximations∗
Various adaptive designs have been proposed and applied to clinical trials, bioassay, psychophysics, etc. More and more people have been paying attention to these design methods. Via strong approximations, this paper presents asymptotic properties of several broad families of designs, such as the play-the-winner rule, randomized play-the-winner rule and its generalization to the multi-arm case,...
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...
متن کاملCovariate-adjusted varying coefficient models.
Covariate-adjusted regression was recently proposed for situations where both predictors and response in a regression model are not directly observed, but are observed after being contaminated by unknown functions of a common observable covariate. The method has been appealing because of its flexibility in targeting the regression coefficients under different forms of distortion. We extend this...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2007
ISSN: 0090-5364
DOI: 10.1214/009053606000001424