Maximum likelihood inference for the Cox regression model with applications to missing covariates

DOI10.1016/j.jmva.2009.03.013zbMath1170.62066OpenAlexW2076963638WikidataQ37347184 ScholiaQ37347184MaRDI QIDQ842920

Ming-Hui Chen, Joseph G. Ibrahim, Qui-Man Shao

Publication date: 28 September 2009

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2744117

zbMATH Keywords

partial likelihoodnecessary and sufficient conditionsproportional hazards modelmissing at random (MAR)existence of partial maximum likelihood estimatelung cancer dataMonte Carlo EM algorithm

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Monte Carlo methods (65C05) Estimation in survival analysis and censored data (62N02)

Related Items

Asymptotic distribution theory on pseudo semiparametric maximum likelihood estimator with covariates missing not at random, A Bayesian multi‐risks survival (MRS) model in the presence of double censorings, Variable Selection in the Cox Regression Model with Covariates Missing at Random, Assessing covariate effects using Jeffreys-type prior in the Cox model in the presence of a monotone partial likelihood

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