… marginal Cox model, but we begin with a brief account of survival analysis and the Cox model
… We do not deal with competing risks, but the problem pointed out in this article for survival …

… Obviously, the effect of each covariate X k estimated by any proportional hazards model can
… Note that the Cox regression model assumes a log-linear and additive fun-ction in terms of …

… Cox regression models with mixed effects are characterised by the distribution of the shared
frailty terms. Different distributions have been proposed for the distribution of the shared …

… , or indeed survival analysis … Cox regression analysis and related inference for the case of
compositional exposure variables. We then illustrate the methodology by applying it to model …

… This article describes the fundamental aspects of survival analysis (2) and of the Cox
regression model in particular, and its application in a thoracic surgical research example. …

… 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 …

… 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 …

… The Cox model relies on the assumption of proportional hazards (PH) across different …
of the Cox regression model details and testing of the PH assumption in survival analysis in …

… Using some new flexible regression models, in this monograph, we analyze survival data
of the Gastrointestinal Tumor Study Group (Stablein and Koutrouvelis 1985), the Veteran’s …

… analysis and Cox proportional hazards regression model, which are the most frequently used
methods in survival analysis. … Finally, time-dependent Cox regression can be used for data …