Holling H, Jansen K, Böhning W, Böhning D, Martin S, Sangnawakij P. Estimation of Effect Heterogeneity in Rare Events Meta-Analysis.
Psychometrika 2022;
87:1081-1102. [PMID:
35133554 PMCID:
PMC9433364 DOI:
10.1007/s11336-021-09835-5]
[Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 11/14/2021] [Indexed: 06/14/2023]
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.
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