The derivation of BLUP, ML, REML estimation methods for generalised linear mixed models

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)2963-2980
Journal / PublicationCommunications in Statistics - Theory and Methods
Volume24
Issue number12
Publication statusPublished - 1 Jan 1995
Externally publishedYes

Abstract

This paper presents a unified derivation of BLUP, ML and REML estimation procedures for normally distributed response variables with possibly correlated random components occurring in the mixed model for the mean. The theory is extended to generalised linear mixed models, where the response variable is not necessarily normally distributed but the model may be fitted using a penalised quasi-likelihood approach which mirrors the development in normal theory models. The method is applied to binomially distributed response variables with logit link to a mixed model containing a random component distributed as an AR(1) process. © 1995, Taylor & Francis Group, LLC. All rights reserved.

Research Area(s)

  • generalised mixed models, residual maximum likelihood