Estimating Regression Parameters and Degree of Dependence for Multivariate Failure Time Data

DOI10.1111/j.0006-341X.1999.01078.xzbMath1059.62598OpenAlexW2131294350WikidataQ30649749 ScholiaQ30649749MaRDI QIDQ4668310

Sylvie Chevret, Cédric Mahé

Publication date: 18 April 2005

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.0006-341x.1999.01078.x

zbMATH Keywords

proportional hazards modelfrailty modelcounting processesmarginal hazards modelmultivariate failure time data

Mathematics Subject Classification ID

Related Items (2)

Comparison of Semiparametric Regression Models for Correlated Survival Data Using Simulations ⋮ Parametric and Semiparametric Conditional Shared Gamma Frailty Models with Events Before Study Entry

Cites Work

• Nonparametric inference for a family of counting processes
• A survey of product-integration with a view toward application in survival analysis
• Modelling Paired Survival Data with Covariates
• Life table methods for heterogeneous populations: Distributions describing the heterogeneity
• The Robust Inference for the Cox Proportional Hazards Model
• Multivariate Generalizations of the Proportional Hazards Model
• Bivariate Survival Models Induced by Frailties
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Inferences on the Association Parameter in Copula Models for Bivariate Survival Data
• An Additive Frailty Model for Correlated Life Times
• Statistical models based on counting processes
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Estimating Regression Parameters and Degree of Dependence for Multivariate Failure Time Data