Nonparametric Item Response Models: A Comparison on Recovering True Scores
Abstract Nonparametric procedures are used to add flexibility to models. Three nonparametric item response models have been proposed, but not directly compared: the Kernel smoothing (KS-IRT); the Davidian-Curve (DC-IRT); and the Bayesian semiparametric Rasch model (SP-Rasch). The main aim of the pre...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Universidade de São Francisco
2024-01-01
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| Series: | Psico-USF |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-82712023000400685&tlng=en |
| _version_ | 1797354328543985664 |
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| author | Vithor Rosa Franco Marie Wiberg Rafael Valdece Sousa Bastos |
| author_facet | Vithor Rosa Franco Marie Wiberg Rafael Valdece Sousa Bastos |
| author_sort | Vithor Rosa Franco |
| collection | DOAJ |
| description | Abstract Nonparametric procedures are used to add flexibility to models. Three nonparametric item response models have been proposed, but not directly compared: the Kernel smoothing (KS-IRT); the Davidian-Curve (DC-IRT); and the Bayesian semiparametric Rasch model (SP-Rasch). The main aim of the present study is to compare the performance of these procedures in recovering simulated true scores, using sum scores as benchmarks. The secondary aim is to compare their performances in terms of practical equivalence with real data. Overall, the results show that, apart from the DC-IRT, which is the model that performs the worse, all the other models give results quite similar to those when sum scores are used. These results are followed by a discussion with practical implications and recommendations for future studies. |
| first_indexed | 2024-03-08T13:48:48Z |
| format | Article |
| id | doaj.art-ea88bbe2d2f14a67ae677ea56c01fdbe |
| institution | Directory Open Access Journal |
| issn | 2175-3563 |
| language | English |
| last_indexed | 2024-03-08T13:48:48Z |
| publishDate | 2024-01-01 |
| publisher | Universidade de São Francisco |
| record_format | Article |
| series | Psico-USF |
| spelling | doaj.art-ea88bbe2d2f14a67ae677ea56c01fdbe2024-01-16T07:36:35ZengUniversidade de São FranciscoPsico-USF2175-35632024-01-0128468569610.1590/1413-82712023280403Nonparametric Item Response Models: A Comparison on Recovering True ScoresVithor Rosa Francohttps://orcid.org/0000-0002-8929-3238Marie Wiberghttps://orcid.org/0000-0001-5549-8262Rafael Valdece Sousa Bastoshttps://orcid.org/0000-0003-2444-6982Abstract Nonparametric procedures are used to add flexibility to models. Three nonparametric item response models have been proposed, but not directly compared: the Kernel smoothing (KS-IRT); the Davidian-Curve (DC-IRT); and the Bayesian semiparametric Rasch model (SP-Rasch). The main aim of the present study is to compare the performance of these procedures in recovering simulated true scores, using sum scores as benchmarks. The secondary aim is to compare their performances in terms of practical equivalence with real data. Overall, the results show that, apart from the DC-IRT, which is the model that performs the worse, all the other models give results quite similar to those when sum scores are used. These results are followed by a discussion with practical implications and recommendations for future studies.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-82712023000400685&tlng=enNonparametric item response modelBayesian modelingMonte Carlo simulation |
| spellingShingle | Vithor Rosa Franco Marie Wiberg Rafael Valdece Sousa Bastos Nonparametric Item Response Models: A Comparison on Recovering True Scores Psico-USF Nonparametric item response model Bayesian modeling Monte Carlo simulation |
| title | Nonparametric Item Response Models: A Comparison on Recovering True Scores |
| title_full | Nonparametric Item Response Models: A Comparison on Recovering True Scores |
| title_fullStr | Nonparametric Item Response Models: A Comparison on Recovering True Scores |
| title_full_unstemmed | Nonparametric Item Response Models: A Comparison on Recovering True Scores |
| title_short | Nonparametric Item Response Models: A Comparison on Recovering True Scores |
| title_sort | nonparametric item response models a comparison on recovering true scores |
| topic | Nonparametric item response model Bayesian modeling Monte Carlo simulation |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-82712023000400685&tlng=en |
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