Estimation of regression parameters in missing data problems
نویسنده
چکیده
Abstract: Suppose Y is a response variable, possibly multivariate, with a density function f(y|x, v;β) conditional on the covariates (x, v) where x and v are vectors and β is a vector of unknown parameters. The authors consider the problem of estimating β when data on the covariate vector v are available for all observations while data on the covariate x are missing at random. They compare several estimators with the profile estimator with respect to bias and standard deviation when the response and covariates are discrete or continuous.
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تاریخ انتشار 2005