Evidence map›Paper›PMID 34550583›Full record

SynthesisMethods in molecular biology (Clifton, N.J.)2022

Fixed- and Random-Effects Models.

Steve Kanters

Abstract readMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 44 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 44 pooled it
–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

73 citing papers in PubMed, 44 syntheses or guidelines pooled it.

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  12. Corneal stability comparison between prophylactic cross-linking with laser refractive surgery technique versus laser refractive surgery technique alone for myopia: a meta-analysis.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025
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  13. Evaluating hyperbaric oxygen therapy as an adjunct to corticosteroids in sudden sensorineural hearing loss: a systematic review and meta-analysis.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025
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13 more citing papers are in PubMed but not listed here.

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

1 author.

Steve KantersSchool of Population and Public Health, University of British Columbia, Vancouver, BC, Canada. skanters@raincity-analytics.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deciding whether to use a fixed-effect model or a random-effects model is a primary decision an analyst must make when combining the results from multiple studies through meta-analysis. Both modeling approaches estimate a single effect size of interest. The fixed-effect meta-analysis assumes that all studies share a single common effect and, as a result, all of the variance in observed effect sizes is attributable to sampling error. The random-effects meta-analysis estimates the mean of a distribution of effects, thus assuming that study effect sizes vary from one study to the next. Under this model, variance in observed effect sizes is attributable to both sampling error (within-study variance) and statistical heterogeneity (between-study variance).The most popular meta-analyses involve using a weighted average to combine the study-level effect sizes. Both fixed- and random-effects models use an inverse-variance weight (variance of the observed effect size). However, given the shared between-study variance used in the random-effects model, it leads to a more balanced distribution of weights than under the fixed-effect model (i.e., small studies are given more relative weight and large studies less). The standard error for these estimators also relates to the inverse-variance weights. As such, the standard errors and confidence intervals for the random-effects model are larger and wider than in the fixed-effect analysis. Indeed, in the presence of statistical heterogeneity, fixed-effect models can lead to overly narrow intervals.In addition to commonly used, generalizable models, there are additional fixed-effect models and random-effect models that can be considered. Additional fixed-effect models that are specific to dichotomous data are more robust to issues that arise from sparse data. Furthermore, random-effects models can be expanded upon using generalized linear mixed models so that different covariance structures are used to distribute statistical heterogeneity across multiple parameters. Finally, both fixed- and random-effects modeling can be conducted using a Bayesian framework.

Indexed as

Linear ModelsBayes TheoremBayesian statisticsFixed-effectHeterogeneityInverse-varianceMeta-analysisRandom-effects

Identifiers

PMID34550583

What OpenQuestion holds

Textmetadata
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.