Statistical Methods for Overdispersed Count Data

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.

• 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

Students in statistics, biostatistics, econometrics and professional statisticians with interest in the analysis of count data; Non-statisticians with skills in R softwares (e.g. economists, decision-makers in public health)

1. Generalized Linear Models
   2. Over-Scattered Count Data
   3. Count Data and Inflation of Zeros