Time-dependent coefficients in a Cox-type regression model

The Regression of Glioblastoma Multiforme is Time Dependent in Wild-Type Rat Xenograft Model

Introduction: Glioblastoma multiforme (GBM) is an aggressive case of primary brain cancer which remains among the most fatal tumors worldwide. Although, some in vitro and in vivo models have been developed for a better understanding of GBM behavior; a natural model of GBM would improve the efficiency of experimental models to human GBM tumors. We aimed at the present study to examine the surviv...

Time-dependent covariates in the Cox proportional-hazards regression model.

The Cox proportional-hazards regression model has achieved widespread use in the analysis of time-to-event data with censoring and covariates. The covariates may change their values over time. This article discusses the use of such time-dependent covariates, which offer additional opportunities but must be used with caution. The interrelationships between the outcome and variable over time can ...

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...

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

Model selection for Cox models with time-varying coefficients.

Summary Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on right-censored failure times. Because not all covariate coefficients are time varying, model selection for such models presents an additional challenge, which is to distinguish covariates with time-varying coefficient from those with time-independent coefficient. ...