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Efficient Multiply Robust Imputation Procedures in the Presence of Influential Units (307969)*Sixia Chen, University of Oklahoma Health Sciences Center
David Haziza, University of Montreal
Victoire Michal, McGill University
Keywords: Influential units, Imputation, Multiply robust
Item nonresponse is a common issue in surveys. To reduce the bias of unadjusted estimators, it is common practice to impute the missing values, leading to the creation of a completed data file. In practice, one must also face the problem of influential units in the sample, which make the commonly used estimators of population totals/means very unstable. To reduce the impact of influential units, we develop a robust version of multiply robust estimators using the conditional bias of a unit. The latter is a measure of influence of a unit that accounts for both sampling and nonresponse. We will present the results of a simulation study to show the benefits of the proposed method in terms of bias and efficiency.