Non-parametric adjustment for covariates when estimating a treatment effect

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Non-parametric adjustment for covariates when estimating a treatment effect

We consider a non-parametric model for estimating the effect of a binary treatment on an outcome variable while adjusting for an observed covariate. A naive procedure consists in performing two separate non-parametric regression of the response on the covariate: one with the treated individuals and the other with the untreated. The treatment effect is then obtained by taking the difference betw...

متن کامل

Bias and Sensitivity Analysis When Estimating Treatment Effects from the Cox Model with Omitted Covariates

Omission of relevant covariates can lead to bias when estimating treatment or exposure effects from survival data in both randomized controlled trials and observational studies. This paper presents a general approach to assessing bias when covariates are omitted from the Cox model. The proposed method is applicable to both randomized and non-randomized studies. We distinguish between the effect...

متن کامل

Non-parametric and semiparametric models for missing covariates in parametric regression Abstracts

s Robustness of covariate modeling for the missing covariate problem in parametric regression is studied under the MAR assumption. For a simple missing covariate pattern, non-parametric likelihood is proposed and is shown to yield a consistent and semiparametrically efficient estimator for the regression parameter. Total robustness is achieved in this situation. For more general missing covaria...

متن کامل

Non-parametric and semiparametric models for missing covariates in parametric regression Abstracts

s Robustness of covariate modeling for the missing covariate problem in parametric regression is studied under the MAR assumption. For a simple missing covariate pattern, non-parametric likelihood is proposed and is shown to yield a consistent and semiparametrically efficient estimator for the regression parameter. Total robustness is achieved in this situation. For more general missing covaria...

متن کامل

A non-parametric framework for estimating threshold limit values

BACKGROUND To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. METHODS We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss ...

متن کامل

ذخیره 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: Journal of Nonparametric Statistics

سال: 2006

ISSN: 1048-5252,1029-0311

DOI: 10.1080/10485250600720779