Mixed-effects Tobit joint models for longitudinal data with skewness, detection limits, and measurement errors
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Publication:764433
DOI10.1155/2012/614102zbMath1233.62042OpenAlexW2012532075WikidataQ58910976 ScholiaQ58910976MaRDI QIDQ764433
Yangxin Huang, Getachew A. Dagne
Publication date: 13 March 2012
Published in: Journal of Probability and Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2012/614102
Multivariate distribution of statistics (62H10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Estimation in survival analysis and censored data (62N02)
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Bayesian joint quantile regression for mixed effects models with censoring and errors in covariates ⋮ Likelihood-based quantile mixed effects models for longitudinal data with multiple features via MCEM algorithm ⋮ Joint modeling for mixed-effects quantile regression of longitudinal data with detection limits and covariates measured with error, with application to AIDS studies ⋮ Mixed-effects Models with Skewed Distributions for Time-varying Decay Rate in HIV Dynamics ⋮ Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study
Uses Software
Cites Work
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