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| Bayesian mixed models for longitudinal genetic data: theory, concepts, and simulation studies |
| Wonil Chung, Youngkwang Cho |
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Genomics Inform. 2022;20(1):e8 Published online March 31, 2022 DOI: https://doi.org/10.5808/gi.21080 |
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Bayesian mixed models for longitudinal genetic data: theory, concepts, and simulation studies Genomics & Informatics. 2022;20(1):e8  Bayesian mixed-effects location and scale models for multivariate longitudinal outcomes: an application to ecological momentary assessment data Statistics in Medicine. 2014;34(4):630-651 Bayesian Inference in Semiparametric Mixed Models for Longitudinal Data Biometrics. 2009;66(1):70-78 Bayesian inferences for beta semiparametric-mixed models to analyze longitudinal neuroimaging data Biometrical Journal. 2014;56(4):662-677 Simulation of Longitudinal Exposure Data with Variance-Covariance Structures Based on Mixed Models Risk Analysis. 2012;33(3):469-479 Bayesian quantile regression-based nonlinear mixed-effects joint models for time-to-event and longitudinal data with multiple features Statistics in Medicine. 2016;35(30):5666-5685 Bayesian bent-cable growth mixture tobit models for longitudinal data with skewness and detection limit: application to AIDS studies Statistics in Medicine. 2016;35(28):5302-5314 Mixed Hidden Markov Models for Longitudinal Data: An Overview International Statistical Review. 2011;79(3):427-454 Case Studies Linear Mixed Models for Longitudinal Data. 2009;405-484 Bayesian Latent-Class Mixed-Effect Hybrid Models for Dyadic Longitudinal Data with Non-Ignorable Dropouts Biometrics. 2013;69(4):914-924 |
