Statistical Methods for Overdispersed Count Data
Langue : Anglais
Auteur : Dupuy Jean-Francois
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.
1. A Brief Overview of Linear Models 2. Generalized Linear Models 3. Overdispersion in Count Data 4. Count Data and Zero Inflation
Students in statistics, biostatistics, econometrics and professional statisticians with interest in the analysis of count data
Non-statisticians with skills in R softwares (economists, decision-makers in public health…)
Non-statisticians with skills in R softwares (economists, decision-makers in public health…)
Jean-Francois Dupuy is a Professor at the INSA Rennes since 2011. From 2009 to 2011, he was a Professor at the University La Rochelle in France. In 2002 he obtained a PhD in Applied Mathematics from the University Paris-Descartes.
- 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
Date de parution : 11-2018
Ouvrage de 192 p.
15x22.8 cm
Thème de Statistical Methods for Overdispersed Count Data :
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