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Statistica Sinica 10(2000), 1153-1169



EFFICIENT RANDOM IMPUTATION FOR MISSING DATA

IN COMPLEX SURVEYS




University of Waterloo, Carleton University and Simon Fraser University


Abstract: A simple adjusted random imputation method for handling item nonresponse in complex surveys is presented. This method eliminates the imputation variance of the estimator of a mean or total, and at the same time preserves the distribution of item values. Jackknife and bootstrap variance estimators that depend only on the reported values in the data file are also proposed. It is necessary to identify the respondent and imputed values in the data file as well as the imputation class. Simulation results on the performance of the proposed method in estimating a total and distribution function are also presented.



Key words and phrases: Adjusted imputation, bootstrap, hotdeck, jackknife, mean imputation, stratified multistage sampling.



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