Analysis of time-dependent covariates in failure time data
Related Experiment Video
Updated: Oct 7, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
U Aydemir1, S Aydemir, P Dirschedl
1Department of Biometry and Epidemiology, Ludwig-Maximilians-University, Marchioninistr.15, 81377 München, Germany. aydemir@ibe.med.uni-muenchen.de
Abstract:
In failure time analyses, time-dependent covariates are only rarely used. In some clinical studies, however, consideration of available covariate information over time could be relevant to understanding complex disease processes. We propose the time-dependent Cox model and the linear model of Aalen as two possible approaches for such time-dependent survival analyses. The approaches are illustrated with the data of the Stanford Heart Transplantation Study and a study of malignant glioma. Differences between these models and the baseline analysis are discussed.
Related Concept Videos
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Assumptions of Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Censoring Survival Data
Survival Tree
Building a Survival Tree
Constructing a survival tree begins...
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...

