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Activity Number: 10
Type: Invited
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: Health Policy Statistics Section
Abstract #314468 View Presentation
Title: Using Instrumental Variables to Estimate a Cox's Proportional Hazards Regression Subject to Additive Confounding
Author(s): Todd MacKenzie*
Companies: Dartmouth College
Keywords: hazard ratio ; causal ; censoring
Abstract:

We propose a method for integrating IVs within the framework of Cox's proportional hazards model and demonstrate the conditions under which it recovers the causal effect of treatment. The methodology is based on the approximate orthogonality of an instrument with unobserved confounders among those at risk. We derive an estimator as the solution to an estimating equation that resembles the score equation of the partial likelihood in much the same way as the traditional IV estimator resembles the normal equations. To justify this IV estimator for a Cox model we perform simulations to evaluate its operating characteristics. Finally, we apply the estimator to an observational study of the effect of coronary catheterization on survival.


Authors who are presenting talks have a * after their name.

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