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Full Description
Copula additive distributional regression enables the joint modeling of multiple outcomes, an essential aspect of many real-world research problems. This book provides an accessible overview of this modeling approach, with a particular focus on its implementation in the GJRM R package, developed by the authors. The emphasis is on bivariate responses with empirical illustrations drawn from diverse fields such as health and medicine, epidemiology, economics and social sciences.
Key Features:
Provides a comprehensive overview of joint regression modeling for multiple outcomes, with a focus on bivariate responses
Offers a practical approach with real-world examples from various fields
Demonstrates the implementation of all the discussed models using the GJRM package in R
Includes supplementary resources such as data accessible through the GJRM.data package in R and additional code available on the authors' webpages
This book is designed for graduate students, researchers, practitioners and analysts who are interested in using copula additive distributional regression for the joint modeling of bivariate outcomes. The methodology is accessible to readers with a basic understanding of core statistics and probability, regression, copula modeling and R.
Contents
1. Core concepts in copula regression. 2. Continuous outcomes. 3. Count outcomes . 4. Survival outcomes. 5. Binary outcomes . 6. Ordinal outcomes. 7. Binary outcome with partial observability. 8. Ordinal and continuous outcomes. 9. Binary and continuous outcomes. 10. Binary and count outcomes. 11. Count and continuous outcomes. 12. Binary outcome with binary treatment effect. 13. Time-to-event outcome with binary treatment effect. 14. Binary outcome with missingness not at random.
