Survey Methodology
A note on multiply robust predictive mean matching imputation with complex survey data

by Sixia Chen, David Haziza and Alexander StubblefieldNote 1

  • Release date: June 24, 2021
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Abstract

Predictive mean matching is a commonly used imputation procedure for addressing the problem of item nonresponse in surveys. The customary approach relies upon the specification of a single outcome regression model. In this note, we propose a novel predictive mean matching procedure that allows the user to specify multiple outcome regression models. The resulting estimator is multiply robust in the sense that it remains consistent if one of the specified outcome regression models is correctly specified. The results from a simulation study suggest that the proposed method performs well in terms of bias and efficiency.

Key Words:   Multiple robustness; Nearest-neigbour imputation; Survey data; Variance estimation.

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How to cite

Chen, S., Haziza, D. and Stubblefield, A. (2021). A note on multiply robust predictive mean matching imputation with complex survey data. Survey Methodology, Statistics Canada, Catalogue No. 12-001-X, Vol. 47, No. 1. Paper available at http://www.statcan.gc.ca/pub/12-001-x/2021001/article/00009-eng.htm.

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ISSN : 1492-0921

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Survey Methodology publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves. All papers will be refereed. However, the authors retain full responsibility for the contents of their papers and opinions expressed are not necessarily those of the Editorial Board or of Statistics Canada.

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Published by authority of the Minister responsible for Statistics Canada.

© Her Majesty the Queen in Right of Canada as represented by the Minister of Industry, 2021

Use of this publication is governed by the Statistics Canada Open Licence Agreement.

Catalogue No. 12-001-X

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Table of contents

Abstract - Article main page
Section 1. Introduction
Section 2. Basic setup
Section 3. Proposed method
Section 4. Simulation study
Acknowledgements
References

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