ERIC Number: EJ1322429
Record Type: Journal
Publication Date: 2020
Pages: 18
Abstractor: As Provided
ISBN: N/A
ISSN: EISSN-2079-3200
EISSN: N/A
Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models
Journal of Intelligence, v8 Article 5 2020
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.
Descriptors: Intelligence Tests, Matrices, Bayesian Statistics, Item Response Theory, Cognitive Ability, Models, Robustness (Statistics)
MDPI AG. Klybeckstrasse 64, 4057 Basel, Switzerland. e-mail: indexing@mdpi.com; e-mail: jintelligence@mdpi.com; Web site: https://www.mdpi.com/journal/jintelligence
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: N/A
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Assessments and Surveys: Raven Progressive Matrices
Grant or Contract Numbers: N/A