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| Regressió de Cox amb covariables dependents del temps× | Estimador de supervivència de Kaplan-Meier× | |
|---|---|---|
| Camp | Supervivència | Supervivència |
| Família | Survival analysis | Survival analysis |
| Any d'origen≠ | 1972 | 1958 |
| Autor original≠ | Cox, D. R. (extended formulation by Therneau & Grambsch) | Kaplan, E. L. & Meier, P. |
| Tipus≠ | Semi-parametric hazard regression model | Non-parametric survival estimator |
| Font seminal≠ | Therneau, T. M. & Grambsch, P. M. (2000). Modeling Survival Data: Extending the Cox Model. Springer. DOI ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Àlies | time-varying covariate Cox model, extended Cox model, Zamana Bağlı Kovaryatlı Cox Regresyonu | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Relacionats≠ | 4 | 2 |
| Resum≠ | Time-dependent Cox regression is an extension of the standard Cox proportional hazards model, introduced through the counting-process formulation developed by Therneau and Grambsch (2000), that allows one or more predictor variables to take different values at different points in a subject's follow-up period. It is the method of choice whenever a covariate — such as a laboratory measurement, a medication dose, or a disease severity score — changes over time rather than remaining fixed from study entry. | 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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