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Analysis of mixed data: An overview Alexander R. de Leon and Keumhee Carriere Chough Introduction Early developments in mixed data analysis Joint analysis of mixed outcomes Highlights of book Combining univariate and multivariate random forests for enhancing predictions of mixed outcomes Abdessamad Dine, Denis Larocque, and Francois Bellavance Introduction Predictions from univariate and multivariate random forests Simulation study Discussion Joint tests for mixed traits in genetic association studies Minjung Kwak, Gang Zheng, and Colin O. Wu Introduction Analysis of binary or quantitative traits Joint analysis of mixed traits Application Discussion Bias in factor score regression and a simple solution Takahiro Hoshino and Peter M. Bentler Introduction Model Bias due to estimated factor scores: Factor analysis model Proposed estimation method Simulation studies Application Theoretical details Discussion Joint modeling of mixed count and continuous longitudinal data Jian Kang and Ying Yang Introduction Complete data model Handling missing data problem Application Discussion Factorization and latent variable models for joint analysis of binary and continuous outcomes Armando Teixeira-Pinto and Jaroslaw Harezlak Introduction Clinical trial on bare-metal and drug-eluting stents Separate analyses Factorization models for binary and continuous outcomes Latent variable models for binary and continuous outcomes Software Discussion Regression models for analyzing clustered binary and continuous outcomes under the assumption of exchangeability E. Olusegun George, Dale Bowman, and Qi An Introduction Distribution theory and likelihood representation Parametric models Application to DEHP data Litter-specific joint quantitative risk assessment Discussion Random effects models for joint analysis of repeatedly measured discrete and continuous outcomes Ralitza Gueorguieva Introduction Models Estimation and inference Applications Discussion Hierarchical modeling of endpoints of different types with generalized linear mixed models Christel Faes Introduction Multivariate multi-level models Special cases Likelihood inference Applications Discussion Joint analysis of mixed discrete and continuous outcomes via copula models Beilei Wu, Alexander R. de Leon, and Niroshan Withanage Introduction Joint models via copulas Associations Likelihood estimation Analysis of ethylene glycol toxicity data Discussion Analysis of mixed outcomes in econometrics: Applications in health economics David M. Zimmer Introduction Random effects models Copula models Application to drug spending and health status Application to nondrug spending and drug usage Discussion Sparse Bayesian modeling of mixed econometric data using data augmentation Helga Wagner and Regina Tuchler Introduction Model specification Logit-normal model Modeling material deprivation and household income Estimating consumer behavior from panel data Discussion Bayesian methods for the analysis of mixed categorical and continuous (incomplete) data Michael J. Daniels and Jeremy T. Gaskins Introduction Examples Characterizing dependence (Informative) Priors Incomplete responses General computational issues Analysis of examples Discussion |
