Statistical Methods for Overdispersed Count Data
- 1st Edition - November 19, 2018
- Latest edition
- Author: Jean-Francois Dupuy
- Language: English
Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages… Read more
Description
Description
Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementation. All methods are illustrated on datasets arising in the field of health economics. As several tools have been developed to tackle over-dispersed and zero-inflated data (such as adjustment methods and zero-inflated models), this book covers the topic in a comprehensive and interesting manner.
Key features
Key features
- Includes reading on several levels, including methodology and applications
- Presents the state-of-the-art on the most recent zero-inflated regression models
- Contains a single dataset that is used as a common thread for illustrating all methodologies
- Includes R code that allows the reader to apply methodologies
Readership
Readership
Table of contents
Table of contents
1. A Brief Overview of Linear Models
2. Generalized Linear Models
3. Overdispersion in Count Data
4. Count Data and Zero Inflation
Product details
Product details
- Edition: 1
- Latest edition
- Published: November 19, 2018
- Language: English
About the author
About the author
JD