A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires

By Alexander P. Christensen, Hudson F. Golino, Paul J Silvia. European Journal of Personality, 2019

215 citations recorded by the source corpus.

This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/eac39d716c4212eff1bf44232821e598222eac5f

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Citations in the corpus

Looking up at the curious personality: individual differences in curiosity and openness to experience (2020, background): “Among their other virtues, those models allow researchers to unpack and visually represent the conceptual structure of complex, hierarchical traits [12].”