Diagnostic Classification Models for Testlets: Methods and Theory.
Psychometrika
; 89(3): 851-876, 2024 09.
Article
em En
| MEDLINE
| ID: mdl-38528268
ABSTRACT
Diagnostic classification models (DCMs) have seen wide applications in educational and psychological measurement, especially in formative assessment. DCMs in the presence of testlets have been studied in recent literature. A key ingredient in the statistical modeling and analysis of testlet-based DCMs is the superposition of two latent structures, the attribute profile and the testlet effect. This paper extends the standard testlet DINA (T-DINA) model to accommodate the potential correlation between the two latent structures. Model identifiability is studied and a set of sufficient conditions are proposed. As a byproduct, the identifiability of the standard T-DINA is also established. The proposed model is applied to a dataset from the 2015 Programme for International Student Assessment. Comparisons are made with DINA and T-DINA, showing that there is substantial improvement in terms of the goodness of fit. Simulations are conducted to assess the performance of the new method under various settings.
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Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Psicometria
/
Modelos Estatísticos
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Avaliação Educacional
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article