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Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation

Journal of Official Statistics

Volume 39 (2023): Issue 4 (December 2023)

By: Yong You and Mike Hidiroglou

Open Access

|Dec 2023

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.

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Articles in this issue

DOI: https://doi.org/10.2478/jos-2023-0026 | Journal eISSN: 2001-7367

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Language: English

Page range: 571 - 590

Submitted on: Sep 1, 2022

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Accepted on: Mar 1, 2023

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Published online: Dec 10, 2023

Published in print: Dec 1, 2023

Published by: Sciendo

In partnership with: Paradigm Publishing Services

Keywords:

Coefficient of variation,

generalized variance function,

log-linear model,

Related subjects:

Probability and statistics

© 2023 Yong You, Mike Hidiroglou, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 39 (2023): Issue 4 (December 2023)

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