Analysis of an Intelligence Dataset
In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series...
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| Format: | Online |
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| Langue: | anglais |
| Publié: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Sujets: | |
| Accès en ligne: | ONIX_20210501_9783036500409_121 |
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| _version_ | 1869523614615732224 |
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| collection | Directory of Open Access Books |
| description | In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven’s (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type. |
| format | Online |
| id | doab-20.500.12854ir-68375 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-683752024-03-29T08:00:59Z Analysis of an Intelligence Dataset Myszkowski, Nils Raven matrices Standard Progressive Matrices test dimensionality bi-factor parallel analysis target rotation exploratory graph analysis E-assessment general mental ability nested logit models item-response theory ability-based guessing Standard Progressive Matrices Item Response Theory Bayesian statistics brms Stan R Raven’s progressive matrices intelligence distractors item analysis intelligence tests classical test theory IRT interaction model test-item regression Mokken scale analysis non-parametric item response theory psychometrics invariant item ordering regularized latent class analysis regularization fused regularization fused grouped regularization distractor analysis n/a bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven’s (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type. 2021-05-01T15:08:25Z 2021-05-01T15:08:25Z 2021 book ONIX_20210501_9783036500409_121 9783036500409 9783036500416 https://directory.doabooks.org/handle/20.500.12854/68375 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/3388 https://mdpi.com/books/pdfview/book/3388 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-0041-6 10.3390/books978-3-0365-0041-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036500409 9783036500416 166 Basel, Switzerland open access |
| spellingShingle | Raven matrices Standard Progressive Matrices test dimensionality bi-factor parallel analysis target rotation exploratory graph analysis E-assessment general mental ability nested logit models item-response theory ability-based guessing Standard Progressive Matrices Item Response Theory Bayesian statistics brms Stan R Raven’s progressive matrices intelligence distractors item analysis intelligence tests classical test theory IRT interaction model test-item regression Mokken scale analysis non-parametric item response theory psychometrics invariant item ordering regularized latent class analysis regularization fused regularization fused grouped regularization distractor analysis n/a bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology Analysis of an Intelligence Dataset |
| title | Analysis of an Intelligence Dataset |
| title_full | Analysis of an Intelligence Dataset |
| title_fullStr | Analysis of an Intelligence Dataset |
| title_full_unstemmed | Analysis of an Intelligence Dataset |
| title_short | Analysis of an Intelligence Dataset |
| title_sort | analysis of an intelligence dataset |
| topic | Raven matrices Standard Progressive Matrices test dimensionality bi-factor parallel analysis target rotation exploratory graph analysis E-assessment general mental ability nested logit models item-response theory ability-based guessing Standard Progressive Matrices Item Response Theory Bayesian statistics brms Stan R Raven’s progressive matrices intelligence distractors item analysis intelligence tests classical test theory IRT interaction model test-item regression Mokken scale analysis non-parametric item response theory psychometrics invariant item ordering regularized latent class analysis regularization fused regularization fused grouped regularization distractor analysis n/a bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology |
| topic_facet | Raven matrices Standard Progressive Matrices test dimensionality bi-factor parallel analysis target rotation exploratory graph analysis E-assessment general mental ability nested logit models item-response theory ability-based guessing Standard Progressive Matrices Item Response Theory Bayesian statistics brms Stan R Raven’s progressive matrices intelligence distractors item analysis intelligence tests classical test theory IRT interaction model test-item regression Mokken scale analysis non-parametric item response theory psychometrics invariant item ordering regularized latent class analysis regularization fused regularization fused grouped regularization distractor analysis n/a bic Book Industry Communication::J Society & social sciences::JM Psychology thema EDItEUR::J Society and Social Sciences::JM Psychology |
| url | ONIX_20210501_9783036500409_121 |