<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Sampling variance smoothing is an important topic in small area estimation. In this article, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis and simulation study indicate that the proposed sampling variance smoothing methods perform very well for small area estimation.</p>
</abstract>

Sampling variance smoothing is an important topic in small area estimation. In this article, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis and simulation study indicate that the proposed sampling variance smoothing methods perform very well for small area estimation.

Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Sampling variance smoothing is an important topic in small area estimation. In this article, we propose sampling variance smoothing methods for small area...

Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation

Publié en ligne: 10 déc. 2023

Pages: 571 - 590

Reçu: 01 sept. 2022

Accepté: 01 mars 2023

DOI: https://doi.org/10.2478/jos-2023-0026

Mots clés
Coefficient of variation, design effect, generalized variance function, log-linear model, relative error

© 2023 Yong You et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation

Publié en ligne: 10 déc. 2023

Pages: 571 - 590

Reçu: 01 sept. 2022

Accepté: 01 mars 2023

DOI: https://doi.org/10.2478/jos-2023-0026

Mots clésCoefficient of variation, design effect, generalized variance function, log-linear model, relative error

© 2023 Yong You et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Coefficient of variation, design effect, generalized variance function, log-linear model, relative error