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| Meta-analytic case-crossover design× | Paritettu tapausselä-kontrollitutkimus× | |
|---|---|---|
| Tieteenala | Epidemiologia | Epidemiologia |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1991 (base design); meta-analytic applications from late 1990s onward | 1950s–1970s |
| Kehittäjä≠ | Maclure (case-crossover basis, 1991); meta-analytic extension through environmental epidemiology consortia (1990s–2000s) | Brian MacMahon and others; systematised by Schlesselman (1982) |
| Tyyppi≠ | Observational epidemiological design with meta-analytic synthesis | Observational analytic design |
| Alkuperäislähde≠ | 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 ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755474 |
| Rinnakkaisnimet | pooled case-crossover analysis, case-crossover meta-analysis, MACCO, systematic pooling of case-crossover studies | matched case-referent study, individually matched case-control, pair-matched case-control, matched case-control design |
| Liittyvät≠ | 3 | 5 |
| Tiivistelmä≠ | The meta-analytic case-crossover design combines the within-person control structure of the case-crossover study with formal meta-analytic pooling across multiple studies. Each contributing study uses cases as their own controls by comparing exposure windows immediately preceding an acute event to matched reference windows in the same individual. The pooled approach synthesizes conditional odds ratios across studies, maximizing statistical power and generalizability — commonly applied to short-term environmental exposures such as air pollution, temperature extremes, and drug triggers of acute events. | A matched case-control study is an observational epidemiological design in which each case (a person with the disease or outcome of interest) is paired with one or more controls (persons without the outcome) who share one or more characteristics — such as age, sex, or clinical setting — to control confounding. Exposure history is then compared between cases and their matched controls to estimate the odds ratio of the exposure-disease association. |
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