Analysis of Mixed Data
eBook - PDF

Analysis of Mixed Data

Methods & Applications

  1. 262 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Analysis of Mixed Data

Methods & Applications

Book details
Table of contents
Citations

About This Book

A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. Carefully edited for smooth readability and

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Yes, you can access Analysis of Mixed Data by Alexander R. de Leon, Keumhee Carriere Chough in PDF and/or ePUB format, as well as other popular books in Mathématiques & Probabilités et statistiques. We have over one million books available in our catalogue for you to explore.

Information

Year
2013
ISBN
9781439884720

Table of contents

  1. Front Cover
  2. Dedication
  3. Contents
  4. Preface
  5. Editors
  6. Contributors
  7. List of Figures
  8. List of Tables
  9. 1. Analysis of mixed data: An overview
  10. 2. Combining univariate and multivariate random forests for enhancing predictions of mixed outcomes
  11. 3. Joint tests for mixed traits in genetic association studies
  12. 4. Bias in factor score regression and a simple solution
  13. 5. Joint modeling of mixed count and continuous longitudinal data
  14. 6. Factorization and latent variable models for joint analysis of binary and continuous outcomes
  15. 7. Regression models for analyzing clustered binary and continuous outcomes under the assumption of exchangeability
  16. 8. Random effects models for joint analysis of repeatedly measured discrete and continuous outcomes
  17. 9. Hierarchical modeling of endpoints of different types with generalized linear mixed models
  18. 10. Joint analysis of mixed discrete and continuous outcomes via copula models
  19. 11. Analysis of mixed outcomes in econometrics: Applications in health economics
  20. 12. Sparse Bayesian modeling of mixed econometric data using data augmentation
  21. 13. Bayesian methods for the analysis of mixed categorical and continuous (incomplete) data
  22. Bibliography