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Adaptív klaszterszámbavétel×Ökológiai vizsgálat×
TudományterületKérdőíves felmérések módszertanaEpidemiológia
MódszercsaládProcess / pipelineProcess / pipeline
Keletkezés éve199019th century (Snow 1854); formalised mid-20th century
MegalkotóSteven ThompsonVarious; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues
TípusProbability-based adaptive designObservational epidemiological study
AlapműThompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI ↗Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81. DOI ↗
Alternatív nevekAdaptive Cluster Sampling, Sequential Adaptive Sampling, Network Sampling, Adaptif Küme Örneklemesiaggregate study, correlational study, ecological correlation study, population-level study
Kapcsolódó35
ÖsszefoglalóAdaptive Cluster Sampling (ACS) is a probability-based survey design introduced by Steven K. Thompson in 1990 for estimating the abundance or total of rare, clustered populations. Starting from an initial random sample, the design adaptively adds neighboring units whenever a sampled unit satisfies a predefined condition—such as exceeding a count threshold—thereby concentrating sampling effort exactly where the population of interest occurs. It is most appropriate for ecologists, epidemiologists, and social scientists studying geographically or socially clustered rare phenomena.An ecological study is an observational epidemiological design in which the unit of analysis is a group or population — a country, region, city, or time period — rather than an individual. Exposures and outcomes are measured as aggregates (rates, proportions, or means) and then correlated across groups to generate or evaluate hypotheses about population-level associations between risk factors and disease.
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ScholarGateMódszerek összehasonlítása: Adaptive Sampling · Ecological Study. Letöltve 2026-06-18, forrás: https://scholargate.app/hu/compare