Transformation survival models

Yulia Marchenko (ymarchenko@stata.com)
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Yulia Marchenko: StataCorp LP

2014 Stata Conference from Stata Users Group

Abstract: The Cox proportional hazards model is one of the most popular methods for analyzing survival or failure-time data. The key assumption underlying the Cox model is that of proportional hazards. This assumption may often be violated in practice. Transformation survival models extend the Cox regression methodology to allow for nonproportional hazards. They represent the class of semiparametric linear transformation models, which relates an unknown transformation of the survival time linearly to covariates. In my presentation, I will describe these models and demonstrate how to fit them in Stata.

Date: 2014-08-02
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