Small area estimates for cross-classifications
Small area estimates for cross-classifications
We develop a class of log-linear structural models that is suited to estimation of small area cross-classified counts based on survey data. This allows us to account for various association structures within the data and includes as a special case the restricted log-linear model underlying structure preserving estimation. The effect of survey design can be incorporated into estimation through the specification of an unbiased direct estimator and its associated covariance structure. We illustrate our approach by applying it to estimation of small area labour force characteristics in Norway.
479-496
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Chambers, Raymond L.
29a4d788-a4f9-4ff4-b6d9-0c0e797c3d56
14 April 2004
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Chambers, Raymond L.
29a4d788-a4f9-4ff4-b6d9-0c0e797c3d56
Zhang, Li-Chun and Chambers, Raymond L.
(2004)
Small area estimates for cross-classifications.
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66 (2), .
(doi:10.1111/j.1369-7412.2004.05266.x).
Abstract
We develop a class of log-linear structural models that is suited to estimation of small area cross-classified counts based on survey data. This allows us to account for various association structures within the data and includes as a special case the restricted log-linear model underlying structure preserving estimation. The effect of survey design can be incorporated into estimation through the specification of an unbiased direct estimator and its associated covariance structure. We illustrate our approach by applying it to estimation of small area labour force characteristics in Norway.
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Published date: 14 April 2004
Organisations:
Social Statistics & Demography
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Local EPrints ID: 356395
URI: http://eprints.soton.ac.uk/id/eprint/356395
ISSN: 1369-7412
PURE UUID: 316c15f8-ce2e-4636-bb08-f07a89974a9a
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Date deposited: 18 Nov 2013 13:58
Last modified: 15 Mar 2024 03:45
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Author:
Raymond L. Chambers
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