Doubly Robust Additive Hazards Models to Estimate Effects of a Continuous Exposure on Survival.

ABSTRACT:

Background

The effect of an exposure on survival can be biased when the regression model is misspecified. Hazard difference is easier to use in risk assessment than hazard ratio and has a clearer interpretation in the assessment of effect modifications.

Methods

We proposed two doubly robust additive hazards models to estimate the causal hazard difference of a continuous exposure on survival. The first model is an inverse probability-weighted additive hazards regression. The second model is an extension of the doubly robust estimator for binary exposures by categorizing the continuous exposure. We compared these with the marginal structural model and outcome regression with correct and incorrect model specifications using simulations. We applied doubly robust additive hazard

SUBMITTER: Wang Y 

PROVIDER: S-EPMC5737934 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature