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Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models
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 ap...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7151098/ https://www.ncbi.nlm.nih.gov/pubmed/32033073 http://dx.doi.org/10.3390/jintelligence8010005 |
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author | Bürkner, Paul-Christian |
author_facet | Bürkner, Paul-Christian |
author_sort | Bürkner, Paul-Christian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7151098 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-71510982020-04-20 Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models Bürkner, Paul-Christian J Intell Article 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. MDPI 2020-02-04 /pmc/articles/PMC7151098/ /pubmed/32033073 http://dx.doi.org/10.3390/jintelligence8010005 Text en © 2020 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Bürkner, Paul-Christian Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models |
title | Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models |
title_full | Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models |
title_fullStr | Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models |
title_full_unstemmed | Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models |
title_short | Analysing Standard Progressive Matrices (SPM-LS) with Bayesian Item Response Models |
title_sort | analysing standard progressive matrices (spm-ls) with bayesian item response models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7151098/ https://www.ncbi.nlm.nih.gov/pubmed/32033073 http://dx.doi.org/10.3390/jintelligence8010005 |
work_keys_str_mv | AT burknerpaulchristian analysingstandardprogressivematricesspmlswithbayesianitemresponsemodels |