Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Адаптивная модель пропорциональных рисков Кокса× | Оценщик Каплана-Майера× | |
|---|---|---|
| Область≠ | Эпидемиология | Анализ выживаемости |
| Семейство≠ | Process / pipeline | Survival analysis |
| Год появления≠ | 2007 (adaptive LASSO variant); base Cox model 1972 | 1958 |
| Автор метода≠ | Hao Helen Zhang & Wenbin Lu (adaptive LASSO formulation); base Cox model by David R. Cox | Kaplan, E. L. & Meier, P. |
| Тип≠ | Penalized semi-parametric survival regression | Non-parametric survival estimator |
| Основополагающий источник≠ | Zhang, H. H., & Lu, W. (2007). Adaptive Lasso for Cox's proportional hazards model. Biometrika, 94(3), 691–703. DOI ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Другие названия≠ | adaptive Cox model, adaptive LASSO Cox regression, penalized Cox proportional hazards, adaptive regularized survival regression | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Связанные≠ | 5 | 2 |
| Сводка≠ | The Adaptive Cox Proportional Hazards model extends the classic Cox regression for time-to-event outcomes by adding adaptive LASSO (or related) penalization. It simultaneously estimates hazard ratios and performs variable selection, shrinking irrelevant covariate coefficients exactly to zero. This makes it especially valuable in high-dimensional clinical or genomic datasets where the number of candidate predictors is large relative to the number of events. | 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. |
| ScholarGateНабор данных ↗ |
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