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Incomplete covariates in the Cox model with applications to biological marker data
Author(s) -
Leong Traci,
Lipsitz Stuart R.,
Ibrahim Joseph G.
Publication year - 2001
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/1467-9876.00248
Subject(s) - covariate , proportional hazards model , missing data , statistics , data set , survival analysis , monte carlo method , mathematics , econometrics , computer science
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.