Models and estimation methods for clinical HIV-1 data

DOI10.1016/j.cam.2004.08.017zbMath1072.92029OpenAlexW2032833358MaRDI QIDQ2566214

Davide Verotta

Publication date: 22 September 2005

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2004.08.017

zbMATH Keywords

MAPordinary differential equations modelBayesianMCMCAdherenceHierarchical modelMixed effect

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Medical applications (general) (92C50)

Related Items

Hierarchical Bayesian inference for HIV dynamic differential equation models incorporating multiple treatment factors ⋮ A Bayesian approach in differential equation dynamic models incorporating clinical factors and covariates ⋮ A model incorporating combined RTIs and PIs therapy during early HIV-1 infection ⋮ A dynamic Bayesian nonlinear mixed-effects model of HIV response incorporating medication adherence, drug resistance and covariates ⋮ Modeling long-term longitudinal HIV dynamics with application to an AIDS clinical study ⋮ Long-term HIV dynamic models incorporating drug adherence and resistance to treatment for prediction of virological responses

Uses Software

• NONMEM

Cites Work

• Numerical parameter identifiability and estimability: Integrating identifiability, estimability, and optimal sampling design
• Rational transfer function approximation (with discussion)
• Modeling HIV dynamics and antiviral response with consideration of time-varying drug exposures, adherence and phenotypic sensitivity
• Non-linear dynamics models characterizing long-term virological data from AIDS clinical trials
• Sampling-Based Approaches to Calculating Marginal Densities
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Accurate Approximations for Posterior Moments and Marginal Densities
• Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
• The Bayesian Modeling of Covariates for Population Pharmacokinetic Models
• Physiological Pharmacokinetic Analysis Using Population Modeling and Informative Prior Distributions
• A new look at the statistical model identification
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