Joint modeling of censored longitudinal and event time data

DOI10.1080/02664763.2012.725468OpenAlexW2023244067MaRDI QIDQ5128883

Lisa A. Weissfeld, Francis Pike

Publication date: 26 October 2020

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

Full work available at URL: http://d-scholarship.pitt.edu/7838/1/ETD_Template_pike_FINAL_7_19_11.pdf

zbMATH Keywords

censored datalinear mixed effects modeljoint modelingtime-dependent covariatesurvival analysis with frailty

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

A fast EM algorithm for fitting joint models of a binary response and multiple longitudinal covariates subject to detection limits

Cites Work

• Estimation of Relationships for Limited Dependent Variables
• A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error
• Fully Exponential Laplace Approximations for the Joint Modelling of Survival and Longitudinal Data
• Joint Analysis of Longitudinal Data Comprising Repeated Measures and Times to Events
• Shared parameter models under random effects misspecification
• Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
• Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited
• Joint modelling of longitudinal measurements and event time data
• A Flexible B‐Spline Model for Multiple Longitudinal Biomarkers and Survival

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