Estimation of effect heterogeneity in rare events meta-analysis.

Holling, H., Jansen K., Böhning, W., Böhning, D., Martin, S.

Research article (journal) | Peer reviewed

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 esti- mating effect heterogeneity. The approaches are exemplified on a meta-analytic case study investigating the acceptance of bibliotherapy.

Details about the publication

JournalPsychometrika
Volume87
Page range1081-1102
StatusPublished
Release year2022
DOI10.1007/s11336-021-09835-5
Link to the full texthttps://doi.org/10.1007/s11336-021-09835-5
Keywordseterogeneity variance, count data analysis, nonparametric mixture models, meta-analysis, generalised linear mixed models, rare events

Authors from the University of Münster

Jansen, Katrin
Professorship for statistics and research methods in psychology