مقایسهٔ روش‌ها

	نمونه‌گیری طبقه‌ای	برآورد برای مناطق کوچک (مدل فی-هریوت)
حوزه	روش‌شناسی پیمایش	روش‌شناسی پیمایش
خانواده	Process / pipeline	Regression model
سال پیدایش	1977	1979
پدیدآور	William G. Cochran	Robert Fay & Roger Herriot
نوع	Probability-based survey sampling design	Model-based survey estimator
منبع بنیادین	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.
نام‌های دیگر	Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme	SAE, Model-Based Small Area Estimation, Area-Level Model, Küçük Alan Tahmini
مرتبط	2	2
خلاصه	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.