Empirical Bayes Estimation of the Mean of a Function of the Latent Variable with Applications to the Treatment of Nonresponse

Abstract

We consider the estimation of linear functionals of the mixing distribution in a nonparametric empirical Bayes framework. Our main interest is in situations in which the mixing distribution is only partially identifiable, as may arise in complex sampling situations with nonresponse. We argue that estimating the functional by applying it to the semiparametric maximum likelihood estimator of the mixing distribution is an efficient tool, even when the maximum likelihood estimator is not unique.