Analysis of mixed data : methods & applications

Content: Analysis of mixed data: An overviewAlexander R. de Leon and Keumhee Carriere ChoughIntroductionEarly developments in mixed data analysisJoint analysis of mixed outcomesHighlights of bookCombining univariate and multivariate random forests for enhancing predictions of mixed outcomesAbdessamad Dine, Denis Larocque, and Francois BellavanceIntroductionPredictions from univariate and multivariate random forestsSimulation studyDiscussionJoint tests for mixed traits in genetic association studiesMinjung Kwak, Gang Zheng, and Colin O. WuIntroductionAnalysis of binary or quantitative traitsJoint analysis of mixed traitsApplicationDiscussionBias in factor score regression and a simple solutionTakahiro Hoshino and Peter M. BentlerIntroductionModelBias due to estimated factor scores: Factor analysis modelProposed estimation methodSimulation studiesApplicationTheoretical detailsDiscussionJoint modeling of mixed count and continuous longitudinal dataJian Kang and Ying YangIntroductionComplete data modelHandling missing data problemApplicationDiscussionFactorization and latent variable models for joint analysis of binary and continuous outcomesArmando Teixeira-Pinto and Jaroslaw HarezlakIntroductionClinical trial on bare-metal and drug-eluting stentsSeparate analysesFactorization models for binary and continuous outcomesLatent variable models for binary and continuous outcomesSoftwareDiscussionRegression models for analyzing clustered binary and continuous outcomes under the assumption of exchangeabilityE. Olusegun George, Dale Bowman, and Qi AnIntroductionDistribution theory and likelihood representationParametric modelsApplication to DEHP dataLitter-specific joint quantitative risk assessmentDiscussionRandom effects models for joint analysis of repeatedly measured discrete and continuous outcomesRalitza GueorguievaIntroductionModelsEstimation and inferenceApplicationsDiscussionHierarchical modeling of endpoints of different types with generalized linear mixed modelsChristel FaesIntroductionMultivariate multi-level modelsSpecial casesLikelihood inferenceApplicationsDiscussionJoint analysis of mixed discrete and continuous outcomes via copula modelsBeilei Wu, Alexander R. de Leon, and Niroshan WithanageIntroductionJoint models via copulasAssociationsLikelihood estimationAnalysis of ethylene glycol toxicity dataDiscussionAnalysis of mixed outcomes in econometrics: Applications in health economicsDavid M. ZimmerIntroductionRandom effects modelsCopula modelsApplication to drug spending and health statusApplication to nondrug spending and drug usageDiscussionSparse Bayesian modeling of mixed econometric data using data augmentationHelga Wagner and Regina TuchlerIntroductionModel specificationLogit-normal modelModeling material deprivation and household incomeEstimating consumer behavior from panel dataDiscussionBayesian methods for the analysis of mixed categorical and continuous (incomplete) dataMichael J. Daniels and Jeremy T. GaskinsIntroductionExamplesCharacterizing dependence(Informative) PriorsIncomplete responsesGeneral computational issuesAnalysis of examplesDiscussion