Canadian Journal of Statistics

Estimation of regression parameters in missing data problems

Journal Article


Let Y be a response variable, possibly multivariate, with a density function f (y|x, v; β) conditional on vectors x and v of covariates and a vector β of unknown parameters. The authors consider the problem of estimating β when the values taken by the covariate vector v are available for all observations while some of those taken by the covariate x are missing at random. They compare the profile estimator to several alternatives, both in terms of bias and standard deviation, when the response and covariates are discrete or continuous.

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