Over-dispersion frequently arises in statistical analysis of count data. Among the various causes of over-dispersion, zero-inflation plays a special role. Several tools have been developed to tackle over-dispersed and zero-inflated data (such as adjustment methods, zero-inflated models). This book 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 these methods are illustrated on datasets arising in the field of health economics. Several levels of reading: methodological / appliedAn up-to-date state of the art on the most recent zero-inflated regression modelsOne data set used as common thread for illustrating all methodologiesR code provided to allow the reader to apply the methodologies INDICE: 1. Generalized Linear Models2. Over-Scattered Count Data3. Count Data and Inflation of Zeros
- ISBN: 978-1-78548-266-3
- Editorial: ISTE Press - Elsevier
- Encuadernacion: Cartoné
- Páginas: 160
- Fecha Publicación: 01/05/2018
- Nº Volúmenes: 1
- Idioma: Inglés