Vertaile menetelmiä

	Mukautuva poikkileikkaus-epidemiologinen tutkimus	Adaptive Sampling	Ekologinen tutkimus
Tieteenala	Epidemiologia	Kyselytutkimuksen metodologia	Epidemiologia
Menetelmäperhe	Process / pipeline	Process / pipeline	Process / pipeline
Syntyvuosi	1990s–2000s (formalization of adaptive elements in observational surveys)	1990	19th century (Snow 1854); formalised mid-20th century
Kehittäjä	Conceptual synthesis of adaptive design methods (Wald, 1947; Bauer & Kohne, 1994) with classical cross-sectional epidemiology (MacMahon & Pugh, 1960s)	Steven Thompson	Various; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues
Tyyppi	Observational epidemiological study design	Probability-based adaptive design	Observational epidemiological study
Alkuperäislähde	Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195083439	Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059.	Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81.
Rinnakkaisnimet	adaptive cross-sectional survey, adaptive prevalence study, adaptive epidemiological survey design, adaptive population cross-section	Adaptive Cluster Sampling, Sequential Adaptive Sampling, Network Sampling, Adaptif Küme Örneklemesi	aggregate study, correlational study, ecological correlation study, population-level study
Liittyvät	2	3	5
Tiivistelmä	An adaptive cross-sectional epidemiological study combines the core logic of a cross-sectional survey — measuring exposures and outcomes simultaneously in a defined population at one point in time — with pre-specified adaptive rules that allow modifications to sampling strategy, sample size, or subgroup allocation based on accumulating interim data. The approach preserves the efficiency and speed of a standard cross-sectional design while improving precision for rare exposures or heterogeneous populations by redirecting sampling resources in real time.	Adaptive 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.