Interval-censored failure time data often occur, for example, in clinical trials or longitudinal studies. For the regression analysis of such data, there have been a number of methods proposed based on continuous regression models such as Cox's proportional hazards model. In practice, however, obser
Analysis of time-dependent covariates in failure time data
✍ Scribed by Ülker Aydemir; Sibel Aydemir; Peter Dirschedl
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 120 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
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✦ Synopsis
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. Di!erences between these models and the baseline analysis are discussed.
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