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Media type:
E-Article
Title:
Variance Estimation of Imputed Estimators of Change for Repeated Rotating Surveys
Contributor:
Berger, Yves G.;
Escobar, Emilio L.
Published:
Blackwell Publishing Ltd, 2017
Published in:
International Statistical Review / Revue Internationale de Statistique, 85 (2017) 3, Seite 421-438
Language:
English
ISSN:
0306-7734;
1751-5823
Origination:
Footnote:
Description:
A common problem in survey sampling is to compare two cross-sectional estimates for the same study variable taken from 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 because of the rotation in repeated surveys and imputation. We propose using a multivariate linear regression approach and show how it can be used to accommodate the effect of rotation and imputation. The regression approach gives a 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.