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

Leong Traci | Zendy; Lipsitz Stuart R. | Zendy; Ibrahim Joseph G. | Zendy

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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.

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