Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Ekoloģiskais pētījums vairākos centros× | Ekoloģiskais pētījums× | |
|---|---|---|
| Nozare | Epidemioloģija | Epidemioloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1980s–1990s (formal methodological description) | 19th century (Snow 1854); formalised mid-20th century |
| Autors≠ | Epidemiological tradition; methodologically articulated by Morgenstern (1982) and Susser (1994) | Various; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues |
| Tips≠ | Observational epidemiological study design | Observational epidemiological study |
| Pirmavots≠ | Morgenstern, H. (1982). Uses of ecologic analysis in epidemiologic research. American Journal of Public Health, 72(12), 1336–1344. DOI ↗ | Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81. DOI ↗ |
| Citi nosaukumi | multi-site ecological study, multinational ecological study, pooled ecological analysis, multicenter aggregate study | aggregate study, correlational study, ecological correlation study, population-level study |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | A multicenter ecological study is an observational epidemiological design in which the units of analysis are groups — such as cities, regions, or countries — rather than individuals, and data are pooled from two or more distinct centers or geographic areas. The approach links aggregate exposure measures (e.g., average pollution levels, vaccination coverage rates) to aggregate outcome rates (e.g., disease incidence per 100,000) across multiple populations, enabling comparisons that would be infeasible within any single site. | 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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