Journal of Official Statistics, Vol.23, No.4, 2007. pp. 433Ė452
Non-Bayesian Multiple Imputation
Jan F. Bjornstad1
Abstract:Multiple imputation is a method specifically designed for variance estimation in the presence of missing data. Rubinís combination formula requires that the imputation method is proper, which essentially means that the imputations are random draws from a posterior distribution in a Bayesian framework. In national statistical institutes NSIís like Statistics Norway, the methods used for imputing for nonresponse are typically non-Bayesian, e.g., some kind of stratified hot-deck. Hence, Rubin s method of multiple imputation is not valid and cannot be applied in NSIís. This article deals with the problem of deriving an alternative combination formula that can be applied for imputation methods typically used in NSIís and suggests an approach for studying this problem. Alternative combination formulas are derived for certain response mechanisms and hot-deck type imputation methods.
Keywords:Variance estimation; survey sampling; stratified sampling; logistic regression; nonresponse; hot-deck imputation.
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