1. Analysis of mixed data : an overview / by Alexander R. de Leon and Keumhee Carriře Chough -- 2. Combining univariate and multivariate random forests for enhancing predictions of mixed outcomes / by Abdessamad Dine, Denis Larocque, and Franȯis Bellavance -- 3. Joint tests for mixed traits in genetic association studies / by Minjung Kwak, Gang Zheng, and Colin O. Wu -- 4. Bias in factor score regression and a simple solution / by Takahiro Hoshino and Peter M. Bentler -- 5. Joint modeling of mixed count and continuous longitudinal data / by Jian Kang and Ying Yang -- 6. Factorization and latent variable models for joint analysis of binary and continuous outcomes / by Armando Teixeira-Pinto and Jaroslaw Harezlak -- 7. Regression models for analyzing clustered binary and continuous outcomes under the assumption of exchangeability / by E. Olusegun George, Dale Bowman, and Qi An -- 8. Random effects models for joint analysis of repeatedly measured discrete and continuous outcomes / by Ralitza Gueorguieva -- 9. Hierarchical modeling of endpoints of different types with generalized linear mixed models / by Christel Faes -- 10. Joint analysis of mixed discrete and continuous outcomes via copula models / by Beilei Wu, Alexander R. de Leon, and Niroshan Withanage -- 11. Analysis of mixed outcomes in econometrics : applications in health economics / by David M. Zimmer -- 12. Sparse Bayesian modeling of mixed econometric data using data augmentation / by Helga Wagner and Regina T¿chler -- 13. Bayesian methods for the analysis of mixed categorical and continuous (incomplete) data / by Michael J. Daniels and Jeremy T. Gaskins.