Analysis of Survival Data Having Time-Dependent Covariates

Survival Data Analysis with Time-Dependent Covariates Using Generalized Additive Models

We discuss a flexible method for modeling survival data using penalized smoothing splines when the values of covariates change for the duration of the study. The Cox proportional hazards model has been widely used for the analysis of treatment and prognostic effects with censored survival data. However, a number of theoretical problems with respect to the baseline survival function remain unsol...

Analysis of time-dependent covariates in a regressive relative survival model.

Relative survival is a method for assessing prognostic factors for disease-specific mortality. However, most relative survival models assume that the effect of covariate on disease-specific mortality is fixed-in-time, which may not hold in some studies and requires adapted modelling. We propose an extension of the Esteve et al. regressive relative survival model that uses the counting process a...

postoperative survival in gastric cancer patients and its associated factors: a time dependent covariates model

the gastric cancer in iran is the fourth in the general population. this study was designed to determine the five-year survival rate of gastric cancer patients, and to assess its associated factors. we analyzed the data using a time-dependent covariates model, and recommend it for analyses of similar data. 281 gastric cancer patients with adenocarcinomatous pathology who had been operated on at...

Parametric survival models for interval-censored data with time-dependent covariates.

We present a parametric family of regression models for interval-censored event-time (survival) data that accomodates both fixed (e.g. baseline) and time-dependent covariates. The model employs a three-parameter family of survival distributions that includes the Weibull, negative binomial, and log-logistic distributions as special cases, and can be applied to data with left, right, interval, or...

Space-time models with time-dependent covariates