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Scientific article
Open access
English

Investigating the Structure of the French WISC–V (WISC–VFR) for Five Age Groups Using Psychometric Network Modeling

Published inJournal of Intelligence, vol. 11, no. 8, 160
Publication date2023
First online date2023
Abstract

Since the seminal work of Spearman, exploratory and confirmatory factor analysis represents the standard method of examining the dimensionality of psychological instruments. Recently, within the network psychometrics approach, a new procedure was proposed to estimate the dimensionality of psychological instruments: exploratory graph analysis (EGA). This study investigated the structure of the French Wechsler Intelligence Scale for Children–Fifth Edition (WISC–VFR) with five standardization sample age groups (6–7, 8–9, 10–11, 12–13, and 14–16 years) using EGA. The primary research questions include (a) how many WISC–VFR dimensions are identified in each age subgroup? (b) how are subtest scores associated within the dimensions? Because the number and the content of the dimensions identified by EGA could vary with samples, the secondary research questions include (c) is there evidence of reproducibility and generalizability of the dimensions identified by EGA?We used another procedure called bootstrap exploratory graph analysis (bootEGA). EGA and bootEGA suggested only three dimensions, which are consistent with processing speed, verbal comprehension, and the “old” perceptual reasoning factor. Results did not support the distinction between visual–spatial and fluid reasoning dimensions. EGA and bootEGA represent new tools to assess the construct validity of psychological instruments, such as the WISC–VFR.

eng
Keywords
  • WISC–VFR
  • Psychometric network analysis
  • Exploratory graph analysis (EGA)
  • BootEGA
  • Construct validity
  • Dimensionality
  • Intelligence
  • Age
Citation (ISO format)
LECERF, Thierry, DOLL, Salomé, BASTIEN, Mathilde. Investigating the Structure of the French WISC–V (WISC–VFR) for Five Age Groups Using Psychometric Network Modeling. In: Journal of Intelligence, 2023, vol. 11, n° 8, p. 160. doi: 10.3390/jintelligence11080160
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ISSN of the journal2079-3200
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