Applying a marginalized frailty model to competing risks

DOI10.1080/02664763.2011.595399OpenAlexW1972766374WikidataQ58138250 ScholiaQ58138250MaRDI QIDQ5126956

Stephanie N. Dixon, Victoria Edge, Gerarda A. Darlington

Publication date: 21 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2011.595399

zbMATH Keywords

clusteringcompeting riskssemi-parametricfamilial correlationClayton-Oakes modelcause-specific hazardsmarginalized frailty

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• SAS
• SAS/STAT
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Cites Work

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• A two-stage estimator of the dependence parameter for the Clayton-Oakes model
• Analysis of multivariate survival data
• Competing Risks
• Nonparametric estimation of cause-specific cross hazard ratio with bivariate competing risks data
• Nonparametric Association Analysis of Bivariate Competing-Risks Data
• Multivariate Generalizations of the Proportional Hazards Model
• Bivariate Survival Models Induced by Frailties
• Partial likelihood
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Modelling multivariate failure time associations in the presence of a competing risk
• A Likelihood Based Estimating Equation for the Clayton–Oakes Model with Marginal Proportional Hazards
• Semiparametric Likelihood Estimation in the Clayton–Oakes Failure Time Model
• Estimation of Distribution Function in Bivariate Competing Risk Models
• Competing Risks Analysis of Correlated Failure Time Data
• Statistical models based on counting processes
• Survival analysis. A self-learning text.

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