方法对比
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| 分层抽样× | Fay-Herriot模型（小区域估计）× | |
|---|---|---|
| 领域 | 调查方法论 | 调查方法论 |
| 方法族≠ | Process / pipeline | Regression model |
| 起源年份≠ | 1977 | 1979 |
| 提出者≠ | William G. Cochran | Robert Fay & Roger Herriot |
| 类型≠ | Probability-based survey sampling design | Model-based survey estimator |
| 开创性文献≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7 | Fay, R. E., & Herriot, R. A. (1979). Estimates of income for small places: An application of James-Stein procedures to census data. Journal of the American Statistical Association, 74(366), 269–277. DOI ↗ |
| 别名 | Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme | SAE, Model-Based Small Area Estimation, Area-Level Model, Küçük Alan Tahmini |
| 相关 | 2 | 2 |
| 摘要≠ | Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics. | Small Area Estimation (SAE) refers to statistical techniques that produce reliable estimates for subpopulations — geographical regions, demographic groups, or administrative units — where direct survey samples are too sparse to yield acceptable precision. The Fay-Herriot model, introduced by Robert Fay and Roger Herriot in 1979, is the canonical area-level SAE model. It supplements weak direct survey estimates with auxiliary covariate information through an empirical Bayes or BLUP framework, substantially reducing mean squared error for small domains. |
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