Simultaneous estimation of the mean of a binary variable from a large number of small areas
Simultaneous estimation of the mean of a binary variable from a large number of small areas
We develop a frequentist method of simultaneous small area estimation under hierarchical models. The simultaneous estimator is the best ensemble predictor under the model. It is preferable to the area-specific best predictor when the distribution of the small area parameters is of interest as well. We provide details of application to binary data. We illustrate the proposed methodology on register employment and unemployment data, and validate the results by the true population values.
253-263
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
September 2003
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Zhang, Li-Chun
(2003)
Simultaneous estimation of the mean of a binary variable from a large number of small areas.
Journal of Official Statistics, 19 (3), .
Abstract
We develop a frequentist method of simultaneous small area estimation under hierarchical models. The simultaneous estimator is the best ensemble predictor under the model. It is preferable to the area-specific best predictor when the distribution of the small area parameters is of interest as well. We provide details of application to binary data. We illustrate the proposed methodology on register employment and unemployment data, and validate the results by the true population values.
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Published date: September 2003
Organisations:
Social Statistics & Demography
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Local EPrints ID: 356405
URI: http://eprints.soton.ac.uk/id/eprint/356405
ISSN: 0282-423X
PURE UUID: 7d41bf27-c2b9-47f0-8d16-d93eed15d208
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Date deposited: 18 Nov 2013 14:39
Last modified: 23 Jul 2022 02:06
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