A new package for fitting random effect models

Einbeck, Jochen; Hinde, John; Darnell, Ross

Abstract

Random effects have become a standard concept in statistical modelling over the last decades. They enter a wide range of applications by providing a simple tool to account for such problems as model misspecification, unobserved (latent) variables, unobserved heterogeneity, and the like. One of the most important model classes for the use of random effects is the generalized linear model. Aitkin (1999) noted that “the literature on random effects in generalized linear models is now extensive”, and this is certainly even more true today.

Citation

Einbeck, J., Hinde, J., & Darnell, R. (2007). A new package for fitting random effect models. R news, 7(1), 26-30

• Journal Article Type: Article
• Publication Date: Apr 1, 2007
• Deposit Date: Apr 21, 2016
• Publicly Available Date: Apr 21, 2016
• Journal: R news
• Electronic ISSN: 1609-3631
• Publisher: R Project for Statistical Computing
• Peer Reviewed: Peer Reviewed
• Volume: 7
• Issue: 1
• Pages: 26-30
• Public URL: https://durham-repository.worktribe.com/output/1570585
• Publisher URL: http://www.r-project.org/