Evidence map›Paper›PMID 35133554›Full record

SynthesisPsychometrika2022

Estimation of Effect Heterogeneity in Rare Events Meta-Analysis.

Heinz Holling, Katrin Jansen, Walailuck Böhning, Dankmar Böhning, Susan Martin, Patarawan Sangnawakij

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Psychometrika, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Heinz HollingInstitute of Psychology, University of Münster, Fliednerstr. 21, 48149,  Münster, Germany. holling@uni-muenster.de.ORCID 0000-0002-0311-3970
Katrin JansenInstitute of Psychology, University of Münster, Fliednerstr. 21, 48149,  Münster, Germany.
Walailuck BöhningInstitute of Psychology, University of Münster, Fliednerstr. 21, 48149,  Münster, Germany.
Dankmar BöhningUniversity of Southampton, Southampton, UK.
Susan MartinUniversity of Southampton, Southampton, UK.
Patarawan SangnawakijThammasat University, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Models, StatisticalComputer SimulationPoisson DistributionPsychometricscount data analysisgeneralised linear mixed modelsheterogeneity variancemeta-analysisnonparametric mixture modelsrare events

Identifiers

PMID35133554
PMCPMC9433364

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.