Bivariate Longitudinal Model For The Analysis Of The Evolution Of Hiv Rna And Cd4 Cell Count In Hiv Infection Taking Into Account Left Censoring Of Hiv Rna Measures

DOI10.1081/BIP-120019271zbMath1180.62185WikidataQ56837872 ScholiaQ56837872MaRDI QIDQ4803387

Hélène Jacqmin-Gadda, Rodolphe Thiébaut, Philippe Morlat, Geneviève Chêne, Christine Katlama, Catherine Leport, Dominique Costagliola, Vincent le Moing

Publication date: 2 April 2003

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

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Medical applications (general) (92C50)

Related Items (6)

Practical identifiability of HIV dynamics models ⋮ Joint Modeling of the Clinical Progression and of the Biomarkers' Dynamics Using a Mechanistic Model ⋮ Treatment Monitoring of HIV‐Infected Patients based on Mechanistic Models ⋮ Modeling the dynamics of biomarkers during primary HIV infection taking into account the uncertainty of infection date ⋮ Score Tests for Exploring Complex Models: Application to HIV Dynamics Models ⋮ Maximum Likelihood Estimation in Dynamical Models of HIV

Cites Work

• Random-Effects Models for Longitudinal Data
• A comparison of the random-effects pattern mixture model with last-observation-carried-forward(locf) analysis in longitudinal clinical trials with dropouts
• A Stochastic Model for the Analysis of Bivariate Longitudinal AIDS Data
• Mixed Effects Models with Censored Data with Application to HIV RNA Levels
• Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
• Analysis of left-censored longitudinal data with application to viral load in HIV infection

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