Analysis of time-dependent covariates in failure time data

Stat Med. 1999 Aug 30;18(16):2123-34. doi: 10.1002/(sici)1097-0258(19990830)18:16<2123::aid-sim176>;2-4.


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.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Glioma / mortality
  • Glioma / therapy
  • Heart Transplantation / mortality
  • Humans
  • Karnofsky Performance Status
  • Linear Models*
  • Prognosis
  • Proportional Hazards Models*
  • Randomized Controlled Trials as Topic
  • Software
  • Survival Analysis*
  • Time Factors