Evidence map›Paper›PMID 41235271›Full record

ArticleFrontiers in psychology2025

Comparing the ability of the IAT and of the SC-IAT to account for behavioral outcomes: a re-analysis using linear mixed-effects models.

Ottavia M Epifania, Pasquale Anselmi, Egidio Robusto

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In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Ottavia M EpifaniaDepartment of Psychology and Cognitive Science, University of Trento, Trento, Italy.
Pasquale AnselmiDepartment of Philosophy, Sociology, Education and Applied Psychology, Padova, Italy.
Egidio RobustoDepartment of Philosophy, Sociology, Education and Applied Psychology, Padova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Implicit measures are widely used to indirectly assess psychological constructs and predict behavior. Nonetheless, comparisons of their predictive validity often suffer from methodological limitations, including administration inconsistencies, scoring differences, and unaccounted sources of variability related to data structure and experimental design. Methods: To address these issues, the present study re-analyzes an existing dataset comparing the Implicit Association Test (IAT) and its single-category variant (SC-IAT) using a modeling framework that integrates a Rasch-like parameterization of accuracies and response times while accounting for the fully crossed data structure and the within-subject design. Results: Results partially align with the original findings and further corroborate the higher predictive validity of the IAT, while revealing the specific contribution of one SC-IAT that was likely obscured in traditional scoring approaches.

Indexed as

implicit association testlog-normal modelRasch modelre-analysessingle category implicit association test

Identifiers

PMID41235271
PMCPMC12605245

What OpenQuestion holds

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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.