方法对比

	自适应分层抽样	多阶段抽样
领域	调查方法论	调查方法论
方法族	Process / pipeline	Process / pipeline
起源年份	1990s (formal development from Thompson 1990 onward)	1950s–1960s (formalized in Kish 1965 and Cochran 1977)
提出者	Steven K. Thompson (adaptive sampling); allocation adaptations by Salehi, Seber, and others	Leslie Kish; William G. Cochran
类型	Probability-based adaptive sampling design	Probability sampling design
开创性文献	Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059.	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495
别名	ASS, adaptive stratified design, stratified adaptive sampling, adaptive allocation stratified sampling	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling
相关	6	5
摘要	Adaptive stratified sampling divides the population into strata and then applies an adaptive rule within each stratum: whenever an initially selected unit satisfies a pre-specified condition (e.g., a rare species is found, a variable exceeds a threshold), neighboring or related units are added to the sample. This combines the variance-reduction power of stratification with the ability to concentrate sampling effort where the phenomenon of interest is actually present.	Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage.