An approximate EM algorithm for maximum likelihood estimation in generalized linear mixed models

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

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Original languageEnglish
Pages (from-to)787-798
Journal / PublicationCommunications in Statistics Part B: Simulation and Computation
Volume32
Issue number3
Publication statusPublished - Aug 2003

Abstract

This article considers the maximum likelihood estimation in generalized linear mixed models (GLMMs). Using results from number theory, we propose a numerical EM algorithm to find the maximum likelihood estimates in GLMMs. Details of the steps required by applying the proposed numerical method to the E-step of the EM algorithm are outlined. The performance and efficiency of the proposed method are compared to some commonly used methods discussed in the literature.