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| Дизайн „случай-кръстосан“× | Проучване случай-контрола× | |
|---|---|---|
| Област | Епидемиология | Епидемиология |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1991 | 1950s (formal methodology); precursors in the 1920s |
| Създател≠ | Malcolm Maclure | Janet Lane-Claypon (early precursors, 1926); formalized by Brian MacMahon and Jerome Cornfield in the 1950s–1960s |
| Тип≠ | Observational epidemiological study design | Observational analytic study design |
| Основополагащ източник≠ | Maclure, M. (1991). The case-crossover design: A method for studying transient effects on the risk of acute events. American Journal of Epidemiology, 133(2), 144–153. DOI ↗ | Schlesselman, J.J. (1982). Case-Control Studies: Design, Conduct, Analysis. Oxford University Press. ISBN: 978-0195027860 |
| Други названия | case-crossover study, CCO design, self-matched case study, within-person crossover case study | case-referent study, case-control design, retrospective case-control, case-control analysis |
| Свързани≠ | 3 | 6 |
| Резюме≠ | The case-crossover design is an observational epidemiological method that estimates whether a transient exposure triggers an acute event by comparing each case's exposure during a brief hazard window immediately before the event to their own exposure during earlier control periods. Because each person serves as their own control, all stable personal characteristics are automatically adjusted for, making the design especially powerful for studying intermittent exposures and sudden-onset outcomes such as myocardial infarction, stroke, or injury. | A case-control study is a retrospective observational design in which individuals who have developed a disease or outcome of interest (cases) are compared with individuals who have not (controls) to determine whether prior exposure to a putative risk factor differs between the two groups. The primary measure of association is the odds ratio, which approximates the relative risk when the outcome is rare. Case-control studies are especially efficient for investigating rare diseases and generating etiological hypotheses. |
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