A calibrated imputation method for secondary data analysis of survey data
A calibrated imputation method for secondary data analysis of survey data
In practical survey sampling, missing data are unavoidable due to nonresponse, rejected observations by editing, disclosure control, or outlier suppression. We propose a calibrated imputation approach so that valid point and variance estimates of the population (or domain) totals can be computed by the secondary users using simple complete-sample formulae. This is especially helpful for variance estimation, which generally require additional information and tools that are unavailable to the secondary users. Our approach is natural for continuous variables, where the estimation may be either based on reweighting or imputation, including possibly their outlier-robust extensions. We also propose a multivariate procedure to accommodate the estimation of the covariance matrix between estimated population totals, which facilitates variance estimation of the ratios or differences among the estimated totals. We illustrate the proposed approach using simulation data in supplementary materials that are available online.
analysis of incomplete data, item nonresponse, missing data, variance estimation
1-17
Da Silva, Damiao Nóbrega
ea21670e-be16-41fb-8251-ec25f1f35daf
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
8 December 2019
Da Silva, Damiao Nóbrega
ea21670e-be16-41fb-8251-ec25f1f35daf
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Da Silva, Damiao Nóbrega and Zhang, Li-Chun
(2019)
A calibrated imputation method for secondary data analysis of survey data.
Scandinavian Journal of Statistics, .
(doi:10.1111/sjos.12435).
Abstract
In practical survey sampling, missing data are unavoidable due to nonresponse, rejected observations by editing, disclosure control, or outlier suppression. We propose a calibrated imputation approach so that valid point and variance estimates of the population (or domain) totals can be computed by the secondary users using simple complete-sample formulae. This is especially helpful for variance estimation, which generally require additional information and tools that are unavailable to the secondary users. Our approach is natural for continuous variables, where the estimation may be either based on reweighting or imputation, including possibly their outlier-robust extensions. We also propose a multivariate procedure to accommodate the estimation of the covariance matrix between estimated population totals, which facilitates variance estimation of the ratios or differences among the estimated totals. We illustrate the proposed approach using simulation data in supplementary materials that are available online.
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Accepted/In Press date: 11 November 2019
e-pub ahead of print date: 21 November 2019
Published date: 8 December 2019
Keywords:
analysis of incomplete data, item nonresponse, missing data, variance estimation
Identifiers
Local EPrints ID: 438635
URI: http://eprints.soton.ac.uk/id/eprint/438635
ISSN: 0303-6898
PURE UUID: 1fa01c66-68fd-46f1-9ce9-671dc0f14afd
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Date deposited: 19 Mar 2020 17:36
Last modified: 17 Mar 2024 05:08
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Author:
Damiao Nóbrega Da Silva
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