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Analysis of time‐dependent covariates in failure time data
Author(s) -
Aydemir Ülker,
Aydemir Sibel,
Dirschedl Peter
Publication year - 1999
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(19990830)18:16<2123::aid-sim176>3.0.co;2-4
Subject(s) - covariate , proportional hazards model , survival analysis , accelerated failure time model , computer science , statistics , econometrics , mathematics , machine learning
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. Copyright © 1999 John Wiley & Sons, Ltd.