A Method of Q-Matrix Validation for the Linear Logistic Test Model
The linear logistic test model (LLTM) is a well-recognized psychometric model for examining the components of difficulty in cognitive tests and validating construct theories. The plausibility of the construct model, summarized in a matrix of weights, known as the Q-matrix or weight matrix, is tested...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2017-05-01
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| Series: | Frontiers in Psychology |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00897/full |
| _version_ | 1828392012566495232 |
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| author | Purya Baghaei Christine Hohensinn |
| author_facet | Purya Baghaei Christine Hohensinn |
| author_sort | Purya Baghaei |
| collection | DOAJ |
| description | The linear logistic test model (LLTM) is a well-recognized psychometric model for examining the components of difficulty in cognitive tests and validating construct theories. The plausibility of the construct model, summarized in a matrix of weights, known as the Q-matrix or weight matrix, is tested by (1) comparing the fit of LLTM with the fit of the Rasch model (RM) using the likelihood ratio (LR) test and (2) by examining the correlation between the Rasch model item parameters and LLTM reconstructed item parameters. The problem with the LR test is that it is almost always significant and, consequently, LLTM is rejected. The drawback of examining the correlation coefficient is that there is no cut-off value or lower bound for the magnitude of the correlation coefficient. In this article we suggest a simulation method to set a minimum benchmark for the correlation between item parameters from the Rasch model and those reconstructed by the LLTM. If the cognitive model is valid then the correlation coefficient between the RM-based item parameters and the LLTM-reconstructed item parameters derived from the theoretical weight matrix should be greater than those derived from the simulated matrices. |
| first_indexed | 2024-12-10T07:12:40Z |
| format | Article |
| id | doaj.art-ed4d9a8e87fc48ffb41b5d2427cbf493 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-12-10T07:12:40Z |
| publishDate | 2017-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-ed4d9a8e87fc48ffb41b5d2427cbf4932022-12-22T01:58:01ZengFrontiers Media S.A.Frontiers in Psychology1664-10782017-05-01810.3389/fpsyg.2017.00897248992A Method of Q-Matrix Validation for the Linear Logistic Test ModelPurya Baghaei0Christine Hohensinn1English Department, Mashhad Branch, Islamic Azad UniversityMashhad, IranDepartment of Psychology, University of ViennaVienna, AustriaThe linear logistic test model (LLTM) is a well-recognized psychometric model for examining the components of difficulty in cognitive tests and validating construct theories. The plausibility of the construct model, summarized in a matrix of weights, known as the Q-matrix or weight matrix, is tested by (1) comparing the fit of LLTM with the fit of the Rasch model (RM) using the likelihood ratio (LR) test and (2) by examining the correlation between the Rasch model item parameters and LLTM reconstructed item parameters. The problem with the LR test is that it is almost always significant and, consequently, LLTM is rejected. The drawback of examining the correlation coefficient is that there is no cut-off value or lower bound for the magnitude of the correlation coefficient. In this article we suggest a simulation method to set a minimum benchmark for the correlation between item parameters from the Rasch model and those reconstructed by the LLTM. If the cognitive model is valid then the correlation coefficient between the RM-based item parameters and the LLTM-reconstructed item parameters derived from the theoretical weight matrix should be greater than those derived from the simulated matrices.http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00897/fulllinear logistic test modelRasch modelweight matrixvalidation |
| spellingShingle | Purya Baghaei Christine Hohensinn A Method of Q-Matrix Validation for the Linear Logistic Test Model Frontiers in Psychology linear logistic test model Rasch model weight matrix validation |
| title | A Method of Q-Matrix Validation for the Linear Logistic Test Model |
| title_full | A Method of Q-Matrix Validation for the Linear Logistic Test Model |
| title_fullStr | A Method of Q-Matrix Validation for the Linear Logistic Test Model |
| title_full_unstemmed | A Method of Q-Matrix Validation for the Linear Logistic Test Model |
| title_short | A Method of Q-Matrix Validation for the Linear Logistic Test Model |
| title_sort | method of q matrix validation for the linear logistic test model |
| topic | linear logistic test model Rasch model weight matrix validation |
| url | http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00897/full |
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