A fully nonparametric approach in survival models with explanatory variables

DOI10.1080/03610929508831666zbMath0875.62152OpenAlexW2066098862MaRDI QIDQ4337123

Jean-Louis Golmard, Sylvie Escolano, A. Mallet

Publication date: 19 May 1997

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929508831666

zbMATH Keywords

maximum likelihoodhazard functioncensored datanon parametric estimationsurvival models with covariates

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Cites Work

• Cox's regression model for counting processes: A large sample study
• The geometry of mixture likelihoods: A general theory
• On the convergence properties of the EM algorithm
• Inference for a nonlinear counting process regression model
• Local Likelihood Estimation
• Checking the Cox model with cumulative sums of martingale-based residuals
• Extended Hazard Regression for Censored Survival Data with Covariates: A Spline Approximation for the Baseline Hazard Function
• A maximum likelihood estimation method for random coefficient regression models

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