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Media type:
E-Article
Title:
Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models
Contributor:
Bürkner, Paul-Christian
imprint:
MDPI AG, 2020
Published in:Journal of Intelligence
Language:
English
DOI:
10.3390/jintelligence8010005
ISSN:
2079-3200
Origination:
Footnote:
Description:
<jats:p>Raven’s Standard Progressive Matrices (SPM) test and related matrix-based tests are widely applied measures of cognitive ability. Using Bayesian Item Response Theory (IRT) models, I reanalyzed data of an SPM short form proposed by Myszkowski and Storme (2018) and, at the same time, illustrate the application of these models. Results indicate that a three-parameter logistic (3PL) model is sufficient to describe participants dichotomous responses (correct vs. incorrect) while persons’ ability parameters are quite robust across IRT models of varying complexity. These conclusions are in line with the original results of Myszkowski and Storme (2018). Using Bayesian as opposed to frequentist IRT models offered advantages in the estimation of more complex (i.e., 3–4PL) IRT models and provided more sensible and robust uncertainty estimates.</jats:p>