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Extending Lawson and Robins’ (2021) Guideline for the Evaluation of Jingle and Jangle Fallacies

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The existence of jingle fallacies (equally named constructs/measures that, in fact, assess different constructs) and jangle fallacies (differently named constructs/measures that, in fact, measure the same concept) jeopardizes psychological assessment as both go along with conceptual and assessment-related uncertainties. A guideline presented by Lawson and Robins (2021) helps evaluate the intensity of respective fallacies. While the guideline is well-elaborated, psychometrical aspects regarding (dis)similarities of nomological networks require extensions and differentiations. I recommend two analytical advancements, namely (a) the derivation of correlation difference hypotheses for criteria with which the allegedly jingled (jangled) variables are assumed to be correlated at equal (different) levels and (b) procedures to derive cutoffs for the overall similarity of nomological networks based on the elemental approach (Kay & Arrow, 2022). Considering correlation difference tests, I further outline the importance of power analyses. These extensions help improve the evaluation of assumed jingle and jangle fallacies, arguably increasing the stability and reliability of research findings.
Center for Open Science
Title: Extending Lawson and Robins’ (2021) Guideline for the Evaluation of Jingle and Jangle Fallacies
Description:
The existence of jingle fallacies (equally named constructs/measures that, in fact, assess different constructs) and jangle fallacies (differently named constructs/measures that, in fact, measure the same concept) jeopardizes psychological assessment as both go along with conceptual and assessment-related uncertainties.
A guideline presented by Lawson and Robins (2021) helps evaluate the intensity of respective fallacies.
While the guideline is well-elaborated, psychometrical aspects regarding (dis)similarities of nomological networks require extensions and differentiations.
I recommend two analytical advancements, namely (a) the derivation of correlation difference hypotheses for criteria with which the allegedly jingled (jangled) variables are assumed to be correlated at equal (different) levels and (b) procedures to derive cutoffs for the overall similarity of nomological networks based on the elemental approach (Kay & Arrow, 2022).
Considering correlation difference tests, I further outline the importance of power analyses.
These extensions help improve the evaluation of assumed jingle and jangle fallacies, arguably increasing the stability and reliability of research findings.

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