Finite mixture of nonlinear mixed-effects joint models in the presence of missing and mismeasured covariate, with application to AIDS studies
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Publication:1660194
DOI10.1016/j.csda.2014.04.003zbMath1468.62128OpenAlexW2079471296MaRDI QIDQ1660194
Yangxin Huang, Yiliang Zhu, Xiaosun Lu
Publication date: 15 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2014.04.003
Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)
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Editorial: The third special issue on advances in mixture models ⋮ Health and Income: Theory and Evidence for OECD Countries ⋮ Joint analysis of nonlinear heterogeneous longitudinal data and binary outcome: an application to AIDS clinical studies ⋮ Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies
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Cites Work
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- Inference from iterative simulation using multiple sequences
- A Bayesian Approach to Joint Mixed-Effects Models with a Skew-Normal Distribution and Measurement Errors in Covariates
- A Bayesian method for classification and discrimination
- A Two-Step Approach to Measurement Error in Time-Dependent Covariates in Nonlinear Mixed-Effects Models, With Application to IGF-I Pharmacokinetics
- A Joint Model for Nonlinear Mixed-Effects Models With Censoring and Covariates Measured With Error, With Application to AIDS Studies
- Dealing With Label Switching in Mixture Models
- Population HIV‐1 Dynamics In Vivo: Applicable Models and Inferential Tools for Virological Data from AIDS Clinical Trials
- Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm
- A Mixture Model for Longitudinal Data with Application to Assessment of Noncompliance
- Bayesian Measures of Model Complexity and Fit
- Bayesian Analysis of Linear and Non-Linear Population Models by Using the Gibbs Sampler
- Mixture of Regression Models With Varying Mixing Proportions: A Semiparametric Approach
- Bayesian Mixture Labeling by Highest Posterior Density
- Simultaneous Inference for Semiparametric Nonlinear Mixed‐Effects Models with Covariate Measurement Errors and Missing Responses
- Measurement Error in Nonlinear Models
- Nonparametric Regression Methods for Longitudinal Data Analysis
- Hierarchical Bayesian Methods for Estimation of Parameters in a Longitudinal HIV Dynamic System
- General growth mixture modeling for randomized preventive interventions
