विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| पूर्वव्यापी पारिस्थितिक अध्ययन× | पूर्वव्यापी अनुप्रस्थ-काट्य महामारी विज्ञान अध्ययन× | |
|---|---|---|
| क्षेत्र | महामारी विज्ञान | महामारी विज्ञान |
| परिवार | Process / pipeline | Process / pipeline |
| उद्भव वर्ष≠ | 20th century (formalized ~1980s–1990s) | Mid–late 20th century |
| प्रवर्तक≠ | Epidemiological tradition; formalized by Morgenstern and others | Epidemiology tradition (formalized in mid-20th century; Rothman, Greenland and others) |
| प्रकार≠ | Observational epidemiological design | Observational study design |
| मौलिक स्रोत≠ | 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 |
| उपनाम | 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 |
| संबंधित | 5 | 5 |
| सारांश≠ | 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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