![Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood by John A. Nelder [Repost]](https://pixhost.icu/avaxhome/a2/a6/0035a6a2_medium.jpeg)
Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood by John A. Nelder [Repost]
![Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood by John A. Nelder [Repost]](https://pixhost.icu/avaxhome/a2/a6/0035a6a2.jpeg)
Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) by John A. Nelder
English | July 13, 2006 | ISBN: 1584886315 | 411 Pages | PDF | 6 MB
English | July 13, 2006 | ISBN: 1584886315 | 411 Pages | PDF | 6 MB
Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.
Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible.