Adjusting regression attenuation in the Cox proportional hazards model

In the measurement error Cox proportional hazards model, the naive maximum partial likelihood estimator (MPLE) is asymptotically biased. In this paper, we give the formula of the asymptotic bias for the additive measurement error Cox model. By adjusting for this error, we derive an adjusted MPLE that is less biased. The bias can be further reduced by adjusting for the estimator second and even third time. This estimator has the advantage of being easy to apply. The performance of the proposed estimator is evaluated through a simulation study.