Books  Data Analysis & Modelling  Data Analysis & Statistics 

Overdispersion

  • Offers a style accessible to researchers in a range of disciplines
  • Includes an up-to-date overview of the topic with discussion of the most recent developments
  • Compares the two main approaches to dealing with overdispersion
  • Provides computations using R

By: David Fletcher(Author), Matthew Parry(Author)

200 pages, 30 b/w illustrations

Apple Academic Press

Hardback | 2020 | #233279 | ISBN-13: 9781482231113
Available for pre-order: Due Aug 2020 Details
NHBS Price: £57.99 $77/€66 approx

About this book

In the frequentist framework, a quasi-likelihood approach has long been used as a means of allowing for overdispersion, a common occurrence in many areas of scientific research. An alternative approach is to improve models by including random effects that account for the extra variability. Overdispersion describes both approaches in detail and compares them in terms of the numerical differences for each data set, using several examples involving real data. Additionally, their performance is assessed by simulations based on examples.


Contents

- Introduction
- Generalized Linear Models
- Overdispersion
- Quasi-likelihood
- Generalized Linear Mixed Models
- Bayesian Approach


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