The Prediction Approach to Robust Variance Estimation in Two-Stage Cluster Sampling
作者:
RichardM. Royall,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1986)
卷期:
Volume 81,
issue 393
页码: 119-123
ISSN:0162-1459
年代: 1986
DOI:10.1080/01621459.1986.10478247
出版商: Taylor & Francis Group
关键词: Finite population;Prediction model;Ratio estimator;Robustness
数据来源: Taylor
摘要:
Robust statistics are derived for estimating the error variance when a finite population total or a ratio of totals is estimated from a two-stage cluster sample in which the first-stage sampling fraction is small. The analysis is based on prediction (superpopulation) models that allow for very general correlation structure within clusters. Results are obtained for when all cluster sizes are known and for when sizes are known only for sample clusters. Ratio, regression, and mean-of-ratios statistics are in the class of population total estimators considered.
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