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| Studi Ekologi Retrospektif× | Studi Epidemiologi Retrospektif Potongan Lintang× | |
|---|---|---|
| Bidang | Epidemiologi | Epidemiologi |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 20th century (formalized ~1980s–1990s) | Mid–late 20th century |
| Pencetus≠ | Epidemiological tradition; formalized by Morgenstern and others | Epidemiology tradition (formalized in mid-20th century; Rothman, Greenland and others) |
| Tipe≠ | Observational epidemiological design | Observational study design |
| Sumber perintis≠ | Morgenstern, H. (1998). Ecologic studies. In K. J. Rothman & S. Greenland (Eds.), Modern Epidemiology (2nd ed., pp. 459–480). Lippincott-Raven. link ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Alias | retrospective aggregate study, historical ecological study, retrospective correlational ecological design, population-level retrospective study | retrospective cross-sectional survey, record-based cross-sectional study, retrospective prevalence study, secondary-data cross-sectional study |
| Terkait | 5 | 5 |
| Ringkasan≠ | A retrospective ecological study examines associations between exposures and outcomes using pre-existing aggregate data from defined populations or geographic units. Rather than following individual subjects, the unit of analysis is a group — a country, region, or time period — and all measurements come from historical records already collected before the study began. It is a rapid, low-cost way to generate hypotheses about environmental, social, or policy determinants of disease at the population level. | A retrospective cross-sectional epidemiological study measures the prevalence of exposures and outcomes at a single analytical time point using data that were originally recorded in the past — such as medical records, administrative databases, or disease registries. It combines the snapshot logic of a cross-sectional design with the efficiency of retrospective data access, making it a practical choice when prospective data collection is unfeasible or when large existing datasets are available. |
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