Campus Units
Statistics
Document Type
Article
Publication Version
Published Version
Publication Date
6-2015
Journal or Book Title
Survey Methodology
Volume
41
Issue
1
First Page
21
Last Page
36
Abstract
An area-level model approach to combining information from several sources is considered in the context of small area estimation. At each small area, several estimates are computed and linked through a system of structural error models. The best linear unbiased predictor of the small area parameter can be computed by the general least squares method. Parameters in the structural error models are estimated using the theory of measurement error models. Estimation of mean squared errors is also discussed. The proposed method is applied to the real problem of labor force surveys in Korea.
Rights
Source: Statistics Canada; Survey Methodology; June 2015. Reproduced and distributed on an "as is" basis with the permission of Statistics Canada.
Copyright Owner
Minister of Industry
Copyright Date
2015
Language
en
File Format
application/pdf
Recommended Citation
Kim, Jae Kwang; Park, Seunghwan; and Kim, Seo-young, "Small area estimation combining information from several sources" (2015). Statistics Publications. 117.
https://lib.dr.iastate.edu/stat_las_pubs/117
Included in
Applied Statistics Commons, Design of Experiments and Sample Surveys Commons, Probability Commons, Statistical Methodology Commons
Comments
This article is published as Kim, Jae-kwang, Seunghwan Park, and Seo-young Kim. "Small area estimation combining information from several sources." Survey Methodology 41 (2015). Posted with permission.