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| 다기관 Kaplan-Meier 분석× | Kaplan-Meier 분석× | |
|---|---|---|
| 분야 | 역학 | 역학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1958 (base method); multicenter designs common from 1970s | 1958 |
| 창시자≠ | Edward L. Kaplan and Paul Meier (method); multicenter application developed through large clinical trial consortia from the 1970s onward | Edward L. Kaplan and Paul Meier |
| 유형≠ | Nonparametric survival analysis in a multicenter setting | Nonparametric survival estimator |
| 원전 | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| 별칭 | pooled Kaplan-Meier, multi-site KM analysis, multicenter survival curve analysis, KM pooled analysis | KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve |
| 관련 | 5 | 5 |
| 요약≠ | Multicenter Kaplan-Meier analysis applies the Kaplan-Meier nonparametric estimator to time-to-event data collected from two or more clinical centers. By pooling or stratifying data across sites, it estimates survival functions and compares them between treatment groups while accounting for potential center effects, enabling conclusions with greater statistical power and broader generalizability than single-center studies. | Kaplan-Meier (KM) analysis is a nonparametric method for estimating the survival function from time-to-event data. Introduced by Kaplan and Meier in 1958, it produces the classic step-function survival curve that shows the probability of surviving beyond each observed event time, correctly accounting for censored observations — participants who left the study or had not yet experienced the event by the end of follow-up. It is one of the most widely used techniques in clinical and epidemiological research. |
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