A likelihood based approach for joint modeling of longitudinal trajectories and informative censoring process

DOI10.1080/03610926.2018.1473599OpenAlexW2890588401WikidataQ90396626 ScholiaQ90396626MaRDI QIDQ5866044

Miran A. Jaffa, Ayad A. Jaffa

Publication date: 10 June 2022

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

Full work available at URL: https://europepmc.org/articles/pmc6768558

zbMATH Keywords

maximum likelihood estimationlongitudinal datajoint modelingshared random effectslikelihood-based approachinformative right censoringlatent random variablesbiomarkers of kidney disease

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Semi-Nonparametric Maximum Likelihood Estimation
• Fitting truncated geometric distributions in large scale real world networks
• An estimation method of marginal treatment effects on correlated longitudinal and survival outcomes
• A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error
• Joint frailty models for recurring events and death using maximum penalized likelihood estimation: application on cancer events
• Fully Exponential Laplace Approximations for the Joint Modelling of Survival and Longitudinal Data
• A Semiparametric Likelihood Approach to Joint Modeling of Longitudinal and Time-to-Event Data
• A Bayesian Semiparametric Joint Hierarchical Model for Longitudinal and Survival Data
• Bayesian Approaches to Joint Cure-Rate and Longitudinal Models with Applications to Cancer Vaccine Trials
• Joint Analysis of Longitudinal Data Comprising Repeated Measures and Times to Events
• Shared Frailty Models for Recurrent Events and a Terminal Event
• Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process
• Modeling Longitudinal Data with Nonparametric Multiplicative Random Effects Jointly with Survival Data
• Semiparametric Approaches for Joint Modeling of Longitudinal and Survival Data with Time-Varying Coefficients
• Joint inference for nonlinear mixed-effects models and time to event at the presence of missing data
• Analysis of Longitudinal Data in the Presence of Informative Observational Times and a Dependent Terminal Event, with Application to Medical Cost Data
• Score Test for Conditional Independence Between Longitudinal Outcome and Time to Event Given the Classes in the Joint Latent Class Model
• Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors
• Analysis of incomplete repeated measurements with dependent censoring times
• Semiparametric Stochastic Mixed Models for Longitudinal Data
• A Stochastic Model for Analysis of Longitudinal AIDS Data
• A Joint Model for Survival and Longitudinal Data Measured with Error
• Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome
• Analyzing Recurrent Event Data With Informative Censoring
• Rank Estimation of Treatment Differences Based on Repeated Measurements Subject to Dependent Censoring
• Semiparametric and Nonparametric Regression Analysis of Longitudinal Data
• Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS
• Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
• Joint Modeling of Survival and Longitudinal Data: Likelihood Approach Revisited
• Semiparametric Analysis of Correlated Recurrent and Terminal Events
• Spatial Multistate Transitional Models for Longitudinal Event Data
• A Joint Frailty Model for Survival and Gap Times Between Recurrent Events
• Joint modelling of longitudinal measurements and event time data
• Longitudinal Data Analysis

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