Abstract:
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Imputation is an effective way to handle missing values. In this paper, we propose a nonparametric multiple imputation procedure that makes use of multiple outcome regression models and/or multiple nonresponse models. Our procedure leads to a multiply robust point estimator in the sense that it remains consistent if anyone of these multiple models is correctly specified. A variance estimate is readily obtained by applying the customary rule advocated by Rubin (1987). The asymptotic properties of the proposed method are established. Results from a simulation study, assessing the proposed method in terms of bias, efficiency and coverage probability, support our findings.
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