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| 加权抽样× | 系统抽样× | |
|---|---|---|
| 领域 | 调查方法论 | 调查方法论 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator) | Mid-20th century (Cochran 1953; Kish 1965) |
| 提出者≠ | Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework) | William G. Cochran; formalized in survey sampling theory |
| 类型 | Probability sampling design | Probability sampling design |
| 开创性文献 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| 别名 | probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling | interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling |
| 相关≠ | 6 | 5 |
| 摘要≠ | Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient. | Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity. |
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