Survey Methodology
How to decompose the non-response variance: A total survey error approach

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by Keven Bosa, Serge Godbout, Fraser Mills and Frédéric PicardNote 1

  • Release date: December 20, 2018
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Abstract

When a linear imputation method is used to correct non-response based on certain assumptions, total variance can be assigned to non-responding units. Linear imputation is not as limited as it seems, given that the most common methods – ratio, donor, mean and auxiliary value imputation – are all linear imputation methods. We will discuss the inference framework and the unit-level decomposition of variance due to non-response. Simulation results will also be presented. This decomposition can be used to prioritize non-response follow-up or manual corrections, or simply to guide data analysis.

Key Words:      Total variance; Adaptive design; Imputation.

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How to cite

Bosa, K., Godbout, S., Mills, F. and Picard, F. (2018). How to decompose the non-response variance: A total survey error approach. Survey Methodology, Statistics Canada, Catalogue No. 12-001-X, Vol. 44, No. 2. Paper available at https://www150.statcan.gc.ca/n1/pub/12-001-x/2018002/article/54957-eng.htm.

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ISSN : 1492-0921

Editorial policy

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, 2018

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

Catalogue No. 12-001-X

Frequency: Semi-annual

Ottawa

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Table of contents

Abstract - Article main page
Section 1. Introduction
Section 2. Inference framework
Section 3. Unit-level error decomposition of variance components
Section 4. Simulation study
Section 5. Conclusion
Acknowledgements
Appendix
References

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