เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การศึกษาทางระบาดวิทยาภาคตัดขวาง× | การศึกษาเชิงนิเวศ× | |
|---|---|---|
| สาขาวิชา | ระบาดวิทยา | ระบาดวิทยา |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 1960s (formal codification); widely practiced since mid-20th century | 19th century (Snow 1854); formalised mid-20th century |
| ผู้ริเริ่ม≠ | Classical epidemiology tradition; systematized by Brian MacMahon and Thomas Pugh (1960s) | Various; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues |
| ประเภท≠ | Observational, descriptive/analytic epidemiological design | Observational epidemiological study |
| แหล่งต้นตำรับ≠ | Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195080407 | Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81. DOI ↗ |
| ชื่อเรียกอื่น | prevalence study, cross-sectional survey, transversal study, cross-sectional design | aggregate study, correlational study, ecological correlation study, population-level study |
| ที่เกี่ยวข้อง≠ | 6 | 5 |
| สรุป≠ | A cross-sectional epidemiological study measures the exposure(s) and outcome(s) of interest simultaneously in a defined population at a single point in time (or over a short period). Because there is no follow-up, it is the most efficient observational design for estimating disease prevalence and for generating hypotheses about associations between risk factors and health outcomes. | 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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