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| 혼합 생존 모형× | Kaplan-Meier 생존 추정량× | |
|---|---|---|
| 분야 | 생존분석 | 생존분석 |
| 계열 | Survival analysis | Survival analysis |
| 기원 연도≠ | 1949 | 1958 |
| 창시자≠ | Boag, J. W. | Kaplan, E. L. & Meier, P. |
| 유형≠ | Parametric mixture survival model | Non-parametric survival estimator |
| 원전≠ | Boag, J. W. (1949). Maximum Likelihood Estimates of the Proportion of Patients Cured. Journal of the Royal Statistical Society B, 11(1), 15–53. link ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| 별칭≠ | cure fraction model, cure rate model, bounded cumulative hazard model, İyileşme Modeli (Mixture Cure Model) | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| 관련 | 2 | 2 |
| 요약≠ | The mixture cure model, first proposed by Boag in 1949 for cancer survival data, is a parametric survival model that explicitly accounts for a fraction of subjects who will never experience the event of interest — the so-called cured or immune fraction. It is the appropriate tool whenever the Kaplan-Meier curve levels off into a long, stable plateau rather than continuing to decline, indicating that a proportion of subjects are permanently event-free. | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. |
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