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Variance estimation of imputed estimators of change for repeated rotating surveys

Berger, Yves G. and Emilio L., Escobar (2016) Variance estimation of imputed estimators of change for repeated rotating surveys International Statistical Review (doi:10.1111/insr.12197).

Record type: Article


A common problem in survey sampling is to compare two cross-sectional estimates for the same study variable taken on two different waves or occasions. These cross-sectional estimates often include imputed values to compensate for item non-response. The estimation of the sampling variance of the estimator of change is useful to judge whether the observed change is statistically significant. Estimating the variance of a change is not straightforward due to rotation in repeated surveys. We propose using a multivariate linear regression approach and show how it can be used to accommodate the effect of imputation. The regression approach gives design-consistent estimation of the variance of change when the sampling fraction is small. We illustrate the proposed approach using random hot-deck imputation, although the proposed estimator can be implemented with other imputation techniques.

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Published date: 2016
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Keywords: deterministic imputation, longitudinal surveys, missing data, nonresponse, overlapping samples, unequal inclusion probabilities
Organisations: Statistical Sciences Research Institute


Local EPrints ID: 376675
ISSN: 0306-7734
PURE UUID: dcde073f-5e3e-47f1-9d2a-36d7d46f7c20

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Date deposited: 05 May 2015 14:15
Last modified: 03 Oct 2017 16:39

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Author: Yves G. Berger
Author: Escobar Emilio L.

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