A Psychometric Network Perspective on the Validity and Validation of Personality Trait Questionnaires
Corresponding Author
Alexander P. Christensen
Department of Psychology, University of North Carolina at Greensboro, Greensboro, NC, USA
Correspondence to:
Alexander P. Christensen, Department of Psychology, University of North Carolina at Greensboro, P.O. Box 26170, Greensboro, NC 27402-6170, USA.
Email: apchrist@uncg.edu
Search for more papers by this authorHudson Golino
Department of Psychology, University of Virginia, Charlottesville, VA, USA
Search for more papers by this authorPaul J. Silvia
Department of Psychology, University of North Carolina at Greensboro, Greensboro, NC, USA
Search for more papers by this authorCorresponding Author
Alexander P. Christensen
Department of Psychology, University of North Carolina at Greensboro, Greensboro, NC, USA
Correspondence to:
Alexander P. Christensen, Department of Psychology, University of North Carolina at Greensboro, P.O. Box 26170, Greensboro, NC 27402-6170, USA.
Email: apchrist@uncg.edu
Search for more papers by this authorHudson Golino
Department of Psychology, University of Virginia, Charlottesville, VA, USA
Search for more papers by this authorPaul J. Silvia
Department of Psychology, University of North Carolina at Greensboro, Greensboro, NC, USA
Search for more papers by this authorAbstract
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
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Citing Literature
Special Issue:New approaches towards conceptualizing and assessing personality
November/December 2020
Pages 1095-1108