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| 매칭된 Kaplan-Meier 분석× | 짝짓기 환자-대조군 연구× | |
|---|---|---|
| 분야 | 역학 | 역학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1958 (KM); matched application formalized 1980s–2000s | 1950s–1970s |
| 창시자≠ | Kaplan & Meier (KM method, 1958); matching extensions developed through propensity score methods (Rosenbaum & Rubin, 1983) | Brian MacMahon and others; systematised by Schlesselman (1982) |
| 유형≠ | Nonparametric survival analysis with observational confounder control | Observational analytic design |
| 원전≠ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457-481. DOI ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755474 |
| 별칭 | KM analysis in matched cohorts, propensity-matched survival curves, matched survival analysis, paired Kaplan-Meier | matched case-referent study, individually matched case-control, pair-matched case-control, matched case-control design |
| 관련≠ | 6 | 5 |
| 요약≠ | Matched Kaplan-Meier analysis estimates and compares survival functions in groups that have been pre-balanced through individual or propensity-score matching. By applying the Kaplan-Meier product-limit estimator to matched cohorts or matched pairs, investigators can visualize time-to-event outcomes while controlling for confounders that would otherwise distort treatment or exposure comparisons in observational data. | 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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