Evidence map›Paper›PMID 39803174›Full record

ArticleJournal of cognition2025

How to Run Linear Mixed Effects Analysis for Pairwise Comparisons? A Tutorial and a Proposal for the Calculation of Standardized Effect Sizes.

Marc Brysbaert, Dries Debeer

Abstract read
In one paragraph

Article in Journal of cognition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
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  4. Editorial Journal of Psycholinguistic Research.Journal of psycholinguistic research · 2026
    Article
  5. Article
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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

2 authors.

Marc BrysbaertFaculty of Psychology and Educational Sciences, Ghent University, Belgium.ORCID https://orcid.org/0000-0002-3645-3189
Dries DebeerFaculty of Psychology and Educational Sciences, Ghent University, Belgium.ORCID https://orcid.org/0000-0002-5875-357X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This tutorial provides guidelines for conducting linear mixed effects (LME) analyses for simple designs, aimed at researchers familiar with t-tests, analysis of variance (ANOVA) and linear regression. First, we compare LME analyses with traditional methods when participants are the only source of random variation. We show that LME analysis is more interesting as soon as you have more than one observation per participant per condition. The second section discusses studies where both participants and stimuli are used as sources of random variation, ensuring robust generalization beyond the specific stimuli tested. In our search for standardized effect sizes, we saw that partial eta squared is even less informative for LME than for ANOVA. We present

Indexed as

Face perceptionMathematical modellingStatistical analysis

Identifiers

PMID39803174
PMCPMC11720698

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.