Modeling Correlated Time-Varying Covariate Effects In A Cox-Type Regression Model

Modeling Correlated Time-Varying Covariate Effects In A Cox-Type Regression Model

Building Cox-Type Structured Hazard Regression Models with Time-Varying Effects

In recent years, flexible hazard regression models based on penalised splines have been developed that allow us to extend the classical Cox-model via the inclusion of time-varying and nonparametric effects. Despite their immediate appeal in terms of flexibility, these models introduce additional difficulties when a subset of covariates and the corresponding modelling alternatives have to be cho...

Penalized Estimators in Cox Regression Model

The proportional hazard Cox regression models play a key role in analyzing censored survival data. We use penalized methods in high dimensional scenarios to achieve more efficient models. This article reviews the penalized Cox regression for some frequently used penalty functions. Analysis of medical data namely ”mgus2” confirms the penalized Cox regression performs better than the cox regressi...

On an adaptive test of time-varying effects in Cox regression

Cox’s proportional hazards model is routinely used in many applied fields, expecially in bio–medical research. A common phenomenon in medical settings is the presence of a time-dependency in the effect of one or more explanatory variables. It is then crucial to decide whether a covariate effect is constant, as prescribed by the standard Cox regression model, or not. Although several proposal ap...

Model assisted Cox regression

Semiparametric random censorship (SRC) models (Dikta, 1998), derive their rationale from their ability to gainfully utilize parametric ideas within the random censorship environment. An extension of this approach is developed for Cox regression, producing new estimators of the regression parameter and baseline cumulative hazard function. Under correct parametric specification, the proposed esti...