๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

A large class of models derived from generalized linear models

โœ Scribed by John A. Nelder

Publisher
John Wiley and Sons
Year
1998
Tongue
English
Weight
74 KB
Volume
17
Category
Article
ISSN
0277-6715

No coin nor oath required. For personal study only.

โœฆ Synopsis

Generalized linear models may be extended in several ways. This paper describes five such extensions: (i) generalized additive models; (ii) the use of quasi-likelihood; (iii) joint modelling of mean and dispersion; (iv) introduction of extra random components to give hierarchical generalized linear models; (v) modelling of correlated responses within subjects in longitudinal models. These extensions are largely independent, and so can be combined in many ways to produce a large class of models. Finally, a further extension to dynamic forms of the models is sketched.

๐Ÿ“œ SIMILAR VOLUMES

A review of some extensions to generaliz
A review of some extensions to generalized linear models
โœ J. K. Lindsey ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 137 KB ๐Ÿ‘ 1 views

Although generalized linear models are reasonably well known, they are not as widely used in medical statistics as might be appropriate, with the exception of logistic, log-linear, and some survival models. At the same time, the generalized linear modelling methodology is decidedly outdated in that

Derivation of the linear-logistic model
Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description
โœ Eberhard O. Voit; Rebecca G. Knapp ๐Ÿ“‚ Article ๐Ÿ“… 1997 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 250 KB ๐Ÿ‘ 1 views

The linear-logistic regression model and Cox's proportional hazard model are widely used in epidemiology. Their successful application leaves no doubt that they are accurate reflections of observed disease processes and their associated risks or incidence rates. In spite of their prominence, it is n

Parametric empirical Bayes estimation fo
Parametric empirical Bayes estimation for a class of extended log-linear regression models
โœ Wanzhu Tu; Walter W. Piegorsch ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 155 KB ๐Ÿ‘ 1 views

This paper presents a fully parametric empirical Bayes approach for the analysis of count data, with emphasis on its application to environmental toxicity data. A hierarchical structure for the mean response is developed from a generalized linear model, based on a Poisson distribution. The linear pr