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Autor/inMyszkowski, Nils
TitelA Mokken Scale Analysis of the Last Series of the Standard Progressive Matrices (SPM-LS)
QuelleIn: Journal of Intelligence, 8 (2020), Artikel 22 (15 Seiten)
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ZusatzinformationORCID (Myszkowski, Nils)
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN2079-3200
SchlagwörterIntelligence Tests; Psychometrics; Nonparametric Statistics; Item Response Theory; Scaling; Test Reliability; Scores; Test Items; Scoring; Raven Progressive Matrices
AbstractRaven's Standard Progressive Matrices (Raven 1941) is a widely used 60-item long measure of general mental ability. It was recently suggested that, for situations where taking this test is too time consuming, a shorter version, comprised of only the last series of the Standard Progressive Matrices (Myszkowski and Storme 2018) could be used, while preserving satisfactory psychometric properties (Garcia-Garzon et al. 2019; Myszkowski and Storme 2018). In this study, I argue, however, that some psychometric properties have been left aside by previous investigations. As part of this special issue on the reinvestigation of Myszkowski and Storme's dataset, I propose to use the non-parametric Item Response Theory framework of Mokken Scale Analysis (Mokken 1971, 1997) and its current developments (Sijtsma and van der Ark 2017) to shed new light on the SPM-LS. Extending previous findings, this investigation indicated that the SPM-LS had satisfactory scalability (H=0.469), local independence and reliability (MS=0.841, LCRC=0.874). Further, all item response functions were monotonically increasing, and there was overall evidence for invariant item ordering (H[subscript T]=0.475), supporting the Double Monotonicity Model (Mokken 1997). Item 1, however, appeared problematic in most analyses. I discuss the implications of these results, notably regarding whether to discard item 1, whether the SPM-LS sum scores can confidently be used to order persons, and whether the invariant item ordering of the SPM-LS allows to use a stopping rule to further shorten test administration. (As Provided).
AnmerkungenMDPI AG. Klybeckstrasse 64, 4057 Basel, Switzerland. e-mail: indexing@mdpi.com; e-mail: jintelligence@mdpi.com; Web site: https://www.mdpi.com/journal/jintelligence
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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