… a Cox regression model with the time-fixed covariates centered age, clinical stage and surgery.
The estimated … from the Cox model are in agreement with the decreasing survival curves …

… being amongst the most commonly employed models. We describe a … for survival analysis
regression models, based on learning mixtures of Cox regressions to model individual survival …

… , parametric models estimate the parameter more efficiently than the Cox model. The aim of
this study was to compare the Cox regression model with parametric models in patients with …

… be analyzed with the Cox regression model to estimate its effect on survival time. For this it …
In situations when the proportional hazards assumption of the Cox regression model does not …

… of all three NN methods with that of Cox regression models which included main effects and
… the NN methods outperformed Cox regression. Compared to Cox regression, the Faraggi–…

… For survival analysis methods in which the likelihoods depend on the rank ordering of … for
the handling of ties in the Cox proportional hazards model. Exact likelihoods can be calculated …

… Median survival times and their associated confidence intervals are often used to summarize
the survival outcome of a group of patients in clinical trials with failure-time endpoints. …

… regression models. For the Cox proportional hazards model and in conditional models for
arbitrarily matched or stratified data, diagnostics derived from augmented regression models …

… survival prediction is Cox regression. Two different Cox regression models were fit,
including 1 model … to have linear effects and 1 model which relaxed this assumption by fitting …

… a "one-step" jackknife estimator of variance is asymptotically equivalent to these variance
estimators; thus, we extend the use of the jackknife from a parametric failure time model for an …