Analysis of Mixed Data

Methods & Applications
Herausgeber: de Leon, Alexander R; Chough, Keumhee Carriere

• Broschiertes Buch

Produktbeschreibung

A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications offers a complete and up-to-date introduction to and summary of the fundamental advances and developments in the field. It presents modern methods and case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. All chapters include illustrative examples, many drawn from real-life case studies, and ample cross-references between chapters are included to enable readers to connect the book's various topics and research strands and to facilitate self-study.

Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 262
• Erscheinungstermin: 23. September 2019
• Englisch
• Abmessung: 231mm x 157mm x 20mm
• Gewicht: 386g
• ISBN-13: 9780367380410
• ISBN-10: 0367380412
• Artikelnr.: 57816825

Autorenporträt

Alexander R. de Leon is Associate Professor in the Department of Mathematics and Statistics at the University of Calgary. Originally from the Philippines, he obtained his BSc and MSc, both in Statistics, from the School of Statistics of the University of the Philippines. After a research studentship at Tokyo University of Science, he completed his PhD in Statistics in 2002 at the University of Alberta. His research interests include methods for analyzing correlated data, multivariate models and distances for mixed discrete and continuous outcomes, pseudo- and composite likelihood methods, copula modeling, assessment of diagnostic tests, statistical quality control, and statistical problems in medicine, particularly in ophthalmology. Alex can be reached at [e-mail] Keumhee Carriere Chough is Professor of Statistics in the Department of Mathematical and Statistical Sciences at the University of Alberta. After completing her BSc in Agriculture from Seoul National University, in Seoul, Korea, she earned her MSc from the University of Manitoba, and her PhD in Statistics from the University of Wisconsin-Madison in 1989. Since 1996, she has been with the Department of Mathematical and Statistical Sciences, University of Alberta, after stints as Assistant Professor at the University of Iowa (1990-1992) and University of Manitoba (1992-1996). She was also the Director of the Statistics Consulting Center at the University of Iowa (1990-1992). Her research interests include design and analysis for repeated measures data, missing data methods, high dimensional data analysis methods, multivariate methods, designs for clinical trials, item response data, variable selection methods, and survival analysis. As well, she specializes in such biostatistical methods as small area variation analysis techniques with applications to health care utilization. She has been a Health Scient

Inhaltsangabe

Analysis of Mixed Data: An Overview. Combining Univariate and Multivariate
Random Forests for Enhancing Predictions of Mixed Outcomes. Joint Tests for
Mixed Traits in Genetic Association Studies. Bias in Factor Score
Regression and a Simple Solution. Joint Modeling of Mixed Count and
Continuous Longitudinal Data. Factorization and Latent Variable Models for
Joint Analysis of Binary and Continuous Outcomes. Regression Models for
Analyzing Clustered Binary and Continuous Outcomes under the Assumption of
Exchangeability. Random Effects Models for Joint Analysis of Repeatedly
Measured Discrete and Continuous Outcomes. Hierarchical Modeling of
Endpoints of Different Types with Generalized Linear Mixed Models. Joint
Analysis of Mixed Discrete and Continuous Outcomes via Copula Models.
Analysis of Mixed Outcomes in Econometrics: Applications in Health
Economics. Sparse Bayesian Modeling of Mixed Econometric Data Using Data
Augmentation. Bayesian Methods for the Analysis of Mixed Categorical and
Continuous (Incomplete) Data.