Incomplete covariates in the Cox model with applications to biological marker data

Traci Leong, Stuart R. Lipsitz and Joseph G. Ibrahim

Journal of the Royal Statistical Society Series C, 2001, vol. 50, issue 4, 467-484

Abstract: A common occurrence in clinical trials with a survival end point is missing covariate data. With ignorably missing covariate data, Lipsitz and Ibrahim proposed a set of estimating equations to estimate the parameters of Cox's proportional hazards model. They proposed to obtain parameter estimates via a Monte Carlo EM algorithm. We extend those results to non‐ignorably missing covariate data. We present a clinical trials example with three partially observed laboratory markers which are used as covariates to predict survival.

Date: 2001
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