Investigating Item Parameter Estimation Accuracy in Multidimensional Polytomous Data Under Various Conditions

dc.contributor.authorBüyükkıdık, Serap
dc.contributor.authorAtar, Hakan Yavuz
dc.date.accessioned2025-03-23T19:08:49Z
dc.date.available2025-03-23T19:08:49Z
dc.date.issued2023
dc.departmentSinop Üniversitesi
dc.description.abstractIn this study, the root mean square error values of item parameters’ estimation in a two-dimensional structure condition were examined under different conditions, considering three and five categories with different algorithms (Expe ctati on–Ma ximiz ation , Metropolis–Hastings Robbins–Monro, Quasi-Monte Carlo Expec tatio n–Max imiza tion) . The simulation conditions included two different sample sizes (1500 and 3000) in a two-dimensional structure, three test lengths (12, 24, and 36), three different interdimensional correlations (0.20, 0.50, and 0.80), and two different category numbers (three and five). Analyses were conducted with three algorithms and the graded response model from the multidimensional item response theory in 36 different conditions with 100 replications. When the errors were examined in terms of the root mean square error, an increase in the number of categories resulted in a partial decrease in most item parameters under the condition of 1500 sample size. For researchers conducting analyses in the polytomous multidimensional item response theory, it is recommended to use as large a sample as possible, at least 24 items, five categories, and the Quasi-Monte Carlo Expec tatio n–Max imiza tion algorithm.
dc.identifier.doi10.5152/hayef.2023.23065
dc.identifier.endpage230
dc.identifier.issn2602-4829
dc.identifier.issue3
dc.identifier.startpage221
dc.identifier.trdizinid1280129
dc.identifier.urihttps://doi.org/10.5152/hayef.2023.23065
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1280129
dc.identifier.urihttps://hdl.handle.net/11486/3218
dc.identifier.volume20
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofHayef:journal of education (Online)
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_TR_20250323
dc.subjectMultidimensional item response theory
dc.subjectExpectation–Maximization
dc.subjectgraded response model
dc.subjectMetropolis–Hastings Robbins–Monro
dc.subjectQuasi-Monte Carlo Expectation–Maximization
dc.titleInvestigating Item Parameter Estimation Accuracy in Multidimensional Polytomous Data Under Various Conditions
dc.typeArticle

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