Contributions to the study of Generalized Partial Credit Model

Authors

  • Eduardo Vargas Ferreira Universidade Federal do Paraná (UFPR), Curitiba, Paraná, Brasil
  • Caio Lucidius Naberezny Azevedo Universidade Estadual de Campinas (Unicamp), Campinas, São Paulo, Brasil

DOI:

https://doi.org/10.18222/eae.v0ix.3385

Keywords:

Item Response Theory, Polytomous Models, Generalized Partial Credit Model, Psychometrics.

Abstract

This article covers the most important inferential aspects of the Generalized Partial Credit Model (GPCM) of the Item Response Theory (IRT). It presents a study on one of the main difficulties encountered in the process of estimation and inference of the IRT models, which is the lack of identifiability. In addition, it presents the interpretation of the model parameters and the information function of the item and the test.

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Author Biographies

Eduardo Vargas Ferreira, Universidade Federal do Paraná (UFPR), Curitiba, Paraná, Brasil

Professor do Departamento de Estatística da Universidade Federal do Paraná (UFPR), Curitiba, Paraná, Brasil.

Caio Lucidius Naberezny Azevedo, Universidade Estadual de Campinas (Unicamp), Campinas, São Paulo, Brasil

Professor do Departamento de Estatística da Universidade Estadual de Campinas (Unicamp), Campinas, São Paulo, Brasil.

References

ANDRADE, D. F.; TAVARES, H. R.; VALLE, R. C. Teoria da Resposta ao Item: conceitos e aplicações. In: SIMPÓSIO NACIONAL DE PROBABILIDADE E ESTATÍSTICA (SINAPE), 14., 2000. Caxambu. Anais... São Paulo: ABE, 2000.

CORDEIRO, G. M. Introdução à teoria da verossimilhança. Rio de Janeiro: ABE, 1992.

LORD, F. M. Applications of Item Response Theory to practical testing problems. 1. ed. Hillsdale: Lawrence Erlbaum, 1980.

MATOS, G. S. Modelos multidimensionais da TRI com distribuições assimétricas para os traços latentes. 2008. 134 f. Tese (Doutorado em Ciência) – Instituto de Matemática e Estatística, Universidade de São Paulo – USP, São Paulo, 2008.

MURAKI, E. A generalized partial credit model: application of an EM algorithm. Applied Psychological Measurement, v. 16, n. 2, p. 159-176, 1992.

MURAKI, E. Information function of the generalized partial credit model. Applied Psychological Measurement, v. 17, n. 4, p. 351-363, 1993.

MURAKI, E. A Generalized Partial Credit Model. In: VAN DER LINDEN, W. J. et al. (Ed.). Handbook of modern Item Response Theory. 1. ed. New York: Springer-Verlag, 1997.

RIVERS, D. Identification of multidimensional spatial voting models. Stanford: Department of Political Science, Stanford University, 2003. Mimeografado. SAMEJIMA, F. Normal ogive model on the continuous response level in the multidimensional latent space. Psychometrika, n. 39, p. 111-121, 1974.

SANTOS, A. A. A. dos; PRIMI, R.; TAXA, F. O. S.; VENDRAMINI, C. M. M. O teste de cloze na avaliação da compreensão em leitura. Psicologia: Reflexão e Crítica, v. 15, n. 3, p. 549-560, 2002.

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Published

2017-04-27

How to Cite

Ferreira, E. V., & Azevedo, C. L. N. (2017). Contributions to the study of Generalized Partial Credit Model. Estudos Em Avaliação Educacional, 28(67), 236–254. https://doi.org/10.18222/eae.v0ix.3385

Issue

Vol. 28 No. 67 (2017): jan./abr. 2017

Section

Articles

License

Copyright (c) 2017 Estudos em Avaliação Educacional

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