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Calibrated Weighting for Small Area Estimation

Calibrated Weighting for Small Area Estimation
Calibrated Weighting for Small Area Estimation
Calibrated weighting methods for estimation of survey population characteristics are widely used. At the same time, model-based prediction methods for estimation of small area or domain characteristics are becoming increasingly popular. This paper explores weighting methods based on the mixed models that underpin small area estimates to see whether they can deliver equivalent small area estimation performance when compared with standard prediction methods and superior population level estimation performance when compared with standard calibrated weighting methods. A simple MSE estimator for weighted small area estimation is also developed.
M05/04
Southampton Statistical Sciences Research Institute, University of Southampton
Chambers, R. L.
8a7dccad-7738-408e-a509-2de287bde907
Chambers, R. L.
8a7dccad-7738-408e-a509-2de287bde907

Chambers, R. L. (2005) Calibrated Weighting for Small Area Estimation (S3RI Methodology Working Papers, M05/04) Southampton, UK. Southampton Statistical Sciences Research Institute, University of Southampton 26pp.

Record type: Monograph (Working Paper)

Abstract

Calibrated weighting methods for estimation of survey population characteristics are widely used. At the same time, model-based prediction methods for estimation of small area or domain characteristics are becoming increasingly popular. This paper explores weighting methods based on the mixed models that underpin small area estimates to see whether they can deliver equivalent small area estimation performance when compared with standard prediction methods and superior population level estimation performance when compared with standard calibrated weighting methods. A simple MSE estimator for weighted small area estimation is also developed.

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Published date: 25 January 2005

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Local EPrints ID: 14074
URI: http://eprints.soton.ac.uk/id/eprint/14074
PURE UUID: 4651bce9-0428-4475-ab01-4c8e11eef756

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Date deposited: 26 Jan 2005
Last modified: 15 Mar 2024 05:18

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Contributors

Author: R. L. Chambers

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