Quantile regression-based Bayesian semiparametric mixed-effects models for longitudinal data with non-normal, missing and mismeasured covariate
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Publication:5222401
DOI10.1080/00949655.2015.1057732OpenAlexW1894690275MaRDI QIDQ5222401
Publication date: 1 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2015.1057732
quantile regressionBayesian inferenceasymmetric Laplace distributionskew distributionssemiparametric mixed-effects model
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Bayesian methods for dealing with missing data problems, Regularized Bayesian quantile regression, Bayesian LASSO-Regularized quantile regression for linear regression models with autoregressive errors, Likelihood-based quantile mixed effects models for longitudinal data with multiple features via MCEM algorithm, Bayesian empirical likelihood of quantile regression with missing observations, Joint modeling for mixed-effects quantile regression of longitudinal data with detection limits and covariates measured with error, with application to AIDS studies, Bayesian quantile regression with mixed discrete and nonignorable missing covariates, Bayesian bridge-randomized penalized quantile regression, Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study
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Cites Work
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