Evidence map›Paper›PMID 39900816›Full record

ArticleBehavior research methods2025

Cross-validation and predictive metrics in psychological research: Do not leave out the leave-one-out.

Diego Iglesias, Miguel A Sorrel, Ricardo Olmos

Abstract read
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In one paragraph

Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Diego IglesiasFaculty of Psychology, Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, 6 Iván Pavlov Street, Cantoblanco Campus, 28049, Madrid, Spain. diego.iglesias@uam.es.ORCID 0009-0003-8963-5669
Miguel A SorrelFaculty of Psychology, Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, 6 Iván Pavlov Street, Cantoblanco Campus, 28049, Madrid, Spain.ORCID 0000-0002-5234-5217
Ricardo OlmosFaculty of Psychology, Department of Social Psychology and Methodology, Universidad Autónoma de Madrid, 6 Iván Pavlov Street, Cantoblanco Campus, 28049, Madrid, Spain.ORCID 0000-0002-1298-6861

Funding

Asociación Española de Metodología de las Ciencias del Comportamiento (AEMCCO) AEMCCO-Julio Olea for young researchers 2023Comunidad de Madrid Grant PIPF-2022/COM-26108Comunidad de Madrid Grant SI3/PJI/2021-00258Universidad Autónoma de Madrid Grant FPI-UAM 2022
6 · The paper itself

Abstract

There is growing interest in integrating explanatory and predictive research practices in psychological research. For this integration to be successful, the psychologist's toolkit must incorporate standard procedures that enable a direct estimation of the prediction error, such as cross-validation (CV). Despite their apparent simplicity, CV methods are intricate, and thus it is crucial to adapt them to specific contexts and predictive metrics. This study delves into the performance of different CV methods in estimating the prediction error in the

Indexed as

Behavioral ResearchPsychologyComputer SimulationData Interpretation, StatisticalHumansModels, StatisticalMonte Carlo MethodRegression AnalysisReproducibility of ResultsCross-validationGeneralizationOut-of-samplePrediction

Identifiers

PMID39900816

What OpenQuestion holds

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Registered trials

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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.