Using Frailty Models to Identify the Longitudinal Biomarkers in Survival Analysis

DOI10.1080/03610920903243736zbMath1202.62155OpenAlexW2075841583MaRDI QIDQ3064066

Feng-shou Ko

Publication date: 20 December 2010

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

Full work available at URL: https://doi.org/10.1080/03610920903243736

zbMATH Keywords

repeated measurementssurrogatebiomarkerheterogenuous baseline hazard

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50) Testing in survival analysis and censored data (62N03)

Related Items (2)

Identification of longitudinal biomarkers for survival by a score test derived from a joint model of longitudinal and competing risks data ⋮ Application of trajectories from growth curve in identification of longitudinal biomarker for the multivariate survival data

Cites Work

• A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error
• A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data
• Joint Modeling of Longitudinal and Survival Data via a Common Frailty
• A Joint Model for Survival and Longitudinal Data Measured with Error
• Joint modelling of longitudinal measurements and event time data
• Identification and efficacy of longitudinal markers for survival
• Unnamed Item

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