Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Amostragem por Agrupamento Adaptativo× | Amostragem em Múltiplos Estágios× | |
|---|---|---|
| Área | Metodologia de survey | Metodologia de survey |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1990 | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| Autor original≠ | Steven K. Thompson | Leslie Kish; William G. Cochran |
| Tipo≠ | Probability-based adaptive sampling design | Probability sampling design |
| Fonte seminal≠ | Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI ↗ | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| Outros nomes | ACS, adaptive network sampling, sequential cluster sampling, neighborhood adaptive sampling | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| Relacionados≠ | 6 | 5 |
| Resumo≠ | Adaptive cluster sampling (ACS) is a probability-based design in which an initial random sample of units triggers the inclusion of neighboring units whenever a predefined condition — typically a threshold count of a rare attribute — is satisfied. Developed by Steven K. Thompson in 1990, ACS is especially powerful for estimating the abundance or distribution of rare, spatially clustered populations such as endangered species, disease hotspots, or hard-to-reach social groups. | 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. |
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