Estimation of Effect Heterogeneity in Rare Events Meta-Analysis

Heinz Holling (), Katrin Jansen, Walailuck Böhning, Dankmar Böhning, Susan Martin and Patarawan Sangnawakij
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Heinz Holling: University of Münster
Katrin Jansen: University of Münster
Walailuck Böhning: University of Münster
Dankmar Böhning: University of Southampton
Susan Martin: University of Southampton
Patarawan Sangnawakij: Thammasat University

Psychometrika, 2022, vol. 87, issue 3, No 13, 1102 pages

Abstract: Abstract The paper outlines several approaches for dealing with meta-analyses of count outcome data. These counts are the accumulation of occurred events, and these events might be rare, so a special feature of the meta-analysis is dealing with low counts including zero-count studies. Emphasis is put on approaches which are state of the art for count data modelling including mixed log-linear (Poisson) and mixed logistic (binomial) regression as well as nonparametric mixture models for count data of Poisson and binomial type. A simulation study investigates the performance and capability of discrete mixture models in estimating effect heterogeneity. The approaches are exemplified on a meta-analytic case study investigating the acceptance of bibliotherapy.

Keywords: heterogeneity variance; count data analysis; nonparametric mixture models; meta-analysis; generalised linear mixed models; rare events (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11336-021-09835-5

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