:: Volume 20, Issue 1 (9-2009) ::
مجله‌ی بررسی‌ها 2009, 20(1): 153-191 Back to browse issues page
Non-Bayesian Multiple Imputation
Zahra Rezaei Ghahroodi *
Abstract:   (3505 Views)

 Multiple imputation is a method specifically designed for variance estimation in the presence of missing data. Rubin’s 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 (NSI’s) 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 NSI’s. This article deals with the problem of deriving an alternative combination formula that can be applied for imputation methods typically used in NSI’s 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.
Full-Text [PDF 484 kb]   (1010 Downloads)    
Type of Study: Research | Subject: General
Received: 2009/04/22 | Accepted: 2009/08/8 | Published: 2016/01/16


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Volume 20, Issue 1 (9-2009) Back to browse issues page