Small-area estimation based on natural exponential family quadratic variance function models and survey weights
成果类型：
Article
署名作者：
Ghosh, M; Maiti, T
署名单位：
State University System of Florida; University of Florida; Iowa State University
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/91.1.95
发表日期：
2004
页码：
95112
关键词：
摘要：
We propose pseudo empirical best linear unbiased estimators of small-area means based on natural exponential family quadratic variance function models when the basic data consist of survey-weighted estimators of these means, area-specific covariates and certain summary measures involving the weights. We also provide explicit approximate mean squared errors of these estimators in the spirit of Prasad & Rao (1990), and these estimators can be readily evaluated. A simulation study is undertaken to evaluate the performance of the proposed inferential procedure. We estimate also the proportion of poor children in the 5-17 years age-group for the different counties in one of the states in the United States.