Diagnostics for meta-analysis based ongeneralized linear mixed models

Research output: Contribution to conferenceOther

Abstract

Meta-analysis is the method to combine data coming from multiple studies,with the aim to provide an overall event-risk measure of interest summarizinginformation coming from the studies. In meta-analysis generalized linear mixedmodels (GLMM) are particularly used for a number of measures of interest sincethey allow the true effect size to differ from study to study while accepting binary,discrete as well as continuous response variable. In the present paper some strategiesof influence diagnostics based on log-likelihood are suggested and discussed. Theseare considered for Individual Patient Data, Aggregate Data and their compounding.
Original languageEnglish
Number of pages0
Publication statusPublished - 2012

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