Title

Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework

Campus Units

Statistics

Document Type

Article

Publication Version

Submitted Manuscript

Publication Date

9-2020

Journal or Book Title

Scandinavian Journal of Statistics

Volume

47

Issue

3

First Page

839

Last Page

861

DOI

10.1111/sjos.12429

Abstract

Predictive mean matching imputation is popular for handling item nonresponse in survey sampling. In this article, we study the asymptotic properties of the predictive mean matching estimator of the population mean. For variance estimation, the conventional bootstrap inference for matching estimators with fixed matches has been shown to be invalid due to the nonsmoothness nature of the matching estimator. We propose asymptotically valid replication variance estimation. The key strategy is to construct replicates of the estimator directly based on linear terms, instead of individual records of variables. Extension to nearest neighbor imputation is also discussed. A simulation study confirms that the new procedure provides valid variance estimation.

Comments

This is a manuscript of an article published as Yang, Shu, and Jae Kwang Kim. "Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework." Scandinavian Journal of Statistics 47, no. 3 (2020): 839-861. doi: 10.1111/sjos.12429. Posted with permission.

Copyright Owner

Board of the Foundation of the Scandinavian Journal of Statistics

Language

en

File Format

application/pdf

Published Version

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