Analysing standard progressive matrices (SPM-LS) with Bayesian item response models

Paul Christian Bürkner*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
62 Downloads (Pure)

Abstract

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.

Original languageEnglish
Article number5
Number of pages18
JournalJournal of Intelligence
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Mar 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • Bayesian statistics
  • Brms
  • Item Response Theory
  • R
  • Stan
  • Standard Progressive Matrices

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