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| 실용적 Kaplan-Meier 분석× | 생존 곡선 비교를 위한 로그-순위 검정× | |
|---|---|---|
| 분야≠ | 역학 | 생존분석 |
| 계열≠ | Process / pipeline | Survival analysis |
| 기원 연도≠ | 1958 (estimator); pragmatic application formalized 1967 onward | 1966 |
| 창시자≠ | Kaplan & Meier (estimator, 1958); Schwartz & Lellouch (pragmatic trial framework, 1967) | Mantel, N. |
| 유형≠ | Non-parametric survival estimator within pragmatic study design | Non-parametric hypothesis test |
| 원전≠ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ | Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗ |
| 별칭 | pragmatic KM analysis, real-world Kaplan-Meier, pragmatic survival curve estimation, KM analysis in pragmatic trials | Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi |
| 관련≠ | 5 | 2 |
| 요약≠ | Pragmatic Kaplan-Meier analysis applies the non-parametric Kaplan-Meier product-limit estimator to time-to-event data collected under real-world or pragmatic conditions — diverse populations, routine clinical care, minimal exclusions, and standard-of-care comparators. Unlike explanatory trials designed to isolate a treatment effect under ideal conditions, pragmatic designs accept real-world heterogeneity, and the resulting survival curves reflect the effectiveness of an intervention as it actually performs in clinical practice. | The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful. |
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