Evidence map›Paper›PMID 40150214›Full record

ArticleBehavioral sciences (Basel, Switzerland)2025

Aberrant Responding in Hypothesis Testing: A Threat to Validity or Source of Insight?

Georgios Sideridis, Mohammed H Alghamdi

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 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

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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

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5 · Who and what money

Authors and funding

2 authors.

Georgios SideridisBoston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.
Mohammed H AlghamdiDepartment of Self Development Skills, King Saud University, P.O. Box 2454, Riyadh 11451, Saudi Arabia.

Funding

King Saud University RSPD2025R601
6 · The paper itself

Abstract

Aberrant responding poses a significant challenge in measurement and validity, often distorting well-established relationships between psychological and educational constructs. This study examines how aberrant response patterns influence the relationship between student-teacher relations and students' perceptions of school safety. Using data from 6617 students from the Saudi Arabia Kingdom from the 2022 Programme for International Student Assessment (PISA), we employed the cusp catastrophe model to evaluate the nonlinear dynamics introduced by aberrant responses, as measured by the U3 person-fit index and the number of Guttman errors. Theoretical and empirical support for the cusp model suggests that aberrance functions as a bifurcation parameter, shifting the relationship between student-teacher relations and perceived school safety from predictable linearity to chaotic instability when exceeding a critical threshold in aberrant responding. Results indicate that both the U3 index and the number of Guttman errors significantly contribute to response distortions, confirming the cusp model's superiority over traditional linear and logistic alternatives. These findings suggest that ignoring aberrant responding risks misinterpreting data structures, while properly accounting for it through catastrophe models provides a more nuanced understanding of nonlinear system behavior in educational assessment. The study highlights the importance of person-fit statistics in psychometric evaluations and reinforces the predictive utility of nonlinear models in handling response distortions in large-scale assessments.

Indexed as

aberrant respondingcusp catastrophe modelGuttman errorsnonlinear modelingperson-fit indicesschool safetystudent–teacher relationsU3 index

Identifiers

PMID40150214
PMCPMC11939625

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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.