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Small area estimation under a two-part random effects model with application to estimation of literacy in developing countries

Small area estimation under a two-part random effects model with application to estimation of literacy in developing countries
Small area estimation under a two-part random effects model with application to estimation of literacy in developing countries
This paper considers situations where the target response value is either zero or an observation from a continuous distribution. A typical example analyzed in the paper is the assessment of literacy proficiency with the possible outcome being either zero, indicating illiteracy, or a positive score measuring the level of literacy. Our interest is in how to obtain valid estimates of the average response, or the proportion of positive responses in small areas, for which only small samples or no samples are available. As in other small area estimation problems, the small sample sizes in at least some of the sampled areas and/or the existence of nonsampled areas requires the use of model based methods. Available methods, however, are not suitable for this kind of data because of the mixed distribution of the responses, having a large peak at zero,juxtaposed to a continuous distribution for the rest of the responses. We develop, therefore, a suitable two-part random effects model and show how to fit the model and assess its goodness of fit, and how to compute the small area estimators of interest and measure their precision. The proposed method is illustrated using simulated data and data obtained from a literacy survey conducted in Cambodia.
credibility intervals, generalized linear mixed model, goodness of fit, linear mixed model, MCMC, prediction bias, prediction MSE
0714-0045
235-249
Pfeffermann, Danny
c7fe07a0-9715-42ce-b90b-1d4f2c2c6ffc
Terryn, Bénédicte
74ec2a1c-cab6-4970-9861-eccdf6357872
Moura, Fernando A.S.
aac41811-e7c2-4cc7-80b6-c78c0f3a27d0
Pfeffermann, Danny
c7fe07a0-9715-42ce-b90b-1d4f2c2c6ffc
Terryn, Bénédicte
74ec2a1c-cab6-4970-9861-eccdf6357872
Moura, Fernando A.S.
aac41811-e7c2-4cc7-80b6-c78c0f3a27d0

Pfeffermann, Danny, Terryn, Bénédicte and Moura, Fernando A.S. (2008) Small area estimation under a two-part random effects model with application to estimation of literacy in developing countries. Survey Methodology, 34 (2), 235-249.

Record type: Article

Abstract

This paper considers situations where the target response value is either zero or an observation from a continuous distribution. A typical example analyzed in the paper is the assessment of literacy proficiency with the possible outcome being either zero, indicating illiteracy, or a positive score measuring the level of literacy. Our interest is in how to obtain valid estimates of the average response, or the proportion of positive responses in small areas, for which only small samples or no samples are available. As in other small area estimation problems, the small sample sizes in at least some of the sampled areas and/or the existence of nonsampled areas requires the use of model based methods. Available methods, however, are not suitable for this kind of data because of the mixed distribution of the responses, having a large peak at zero,juxtaposed to a continuous distribution for the rest of the responses. We develop, therefore, a suitable two-part random effects model and show how to fit the model and assess its goodness of fit, and how to compute the small area estimators of interest and measure their precision. The proposed method is illustrated using simulated data and data obtained from a literacy survey conducted in Cambodia.

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More information

Published date: December 2008
Keywords: credibility intervals, generalized linear mixed model, goodness of fit, linear mixed model, MCMC, prediction bias, prediction MSE

Identifiers

Local EPrints ID: 153903
URI: http://eprints.soton.ac.uk/id/eprint/153903
ISSN: 0714-0045
PURE UUID: eed74eb9-782c-40cf-9d95-2956db1a7c1e

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Date deposited: 21 May 2010 15:05
Last modified: 14 Mar 2024 01:32

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Contributors

Author: Bénédicte Terryn
Author: Fernando A.S. Moura

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