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Network structure of the Wisconsin Schizotypy Scales–Short Forms: Examining psychometric network filtering approaches

Christensen, AP; Kenett, YN; Aste, T; Silvia, PJ; Kwapil, TR; (2018) Network structure of the Wisconsin Schizotypy Scales–Short Forms: Examining psychometric network filtering approaches. Behavior Research Methods , 50 (6) pp. 2531-2550. 10.3758/s13428-018-1032-9. Green open access

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Abstract

Schizotypy is a multidimensional construct that provides a useful framework for understanding the etiology, development, and risk for schizophrenia-spectrum disorders. Past research has applied traditional methods, such as factor analysis, to uncovering common dimensions of schizotypy. In the present study, we aimed to advance the construct of schizotypy, measured by the Wisconsin Schizotypy Scales-Short Forms (WSS-SF), beyond this general scope by applying two different psychometric network filtering approaches-the state-of-the-art approach (lasso), which has been employed in previous studies, and an alternative approach (information-filtering networks; IFNs). First, we applied both filtering approaches to two large, independent samples of WSS-SF data (ns = 5,831 and 2,171) and assessed each approach's representation of the WSS-SF's schizotypy construct. Both filtering approaches produced results similar to those from traditional methods, with the IFN approach producing results more consistent with previous theoretical interpretations of schizotypy. Then we evaluated how well both filtering approaches reproduced the global and local network characteristics of the two samples. We found that the IFN approach produced more consistent results for both global and local network characteristics. Finally, we sought to evaluate the predictability of the network centrality measures for each filtering approach, by determining the core, intermediate, and peripheral items on the WSS-SF and using them to predict interview reports of schizophrenia-spectrum symptoms. We found some similarities and differences in their effectiveness, with the IFN approach's network structure providing better overall predictive distinctions. We discuss the implications of our findings for schizotypy and for psychometric network analysis more generally.

Type: Article
Title: Network structure of the Wisconsin Schizotypy Scales–Short Forms: Examining psychometric network filtering approaches
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.3758/s13428-018-1032-9
Publisher version: https://doi.org/10.3758/s13428-018-1032-9
Language: English
Additional information: © Psychonomic Society, Inc. 2018. This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Network analysis, Schizophrenia-spectrum disorders, Schizotypy
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10046405
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