Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/76119
Type: Artigo
Title: A multiple group item response theory model with centered skew-normal latent trait distributions under a Bayesian framework
Author: Santos, Jose R.S.
Azevedo, Caio L.N.
Bolfarine, Heleno
Abstract: Very often, in psychometric research, as in educational assessment, it is necessary to analyze item response from clustered respondents. The multiple group item response theory (IRT) model proposed by Bock and Zimowski [12] provides a useful framework for analyzing such type of data. In this model, the selected groups of respondents are of specific interest such that group-specific population distributions need to be defined. The usual assumption for parameter estimation in this model, which is that the latent traits are random variables following different symmetric normal distributions, has been questioned in many works found in the IRT literature. Furthermore, when this assumption does not hold, misleading inference can result. In this paper, we consider that the latent traits for each group follow different skew-normal distributions, under the centered parameterization. We named it skew multiple group IRT model. This modeling extends the works of Azevedo et al. [4], Bazan et al. [11] and Bock and Zimowski [12] (concerning the latent trait distribution). Our approach ensures that the model is identifiable. We propose and compare, concerning convergence issues, two Monte Carlo Markov Chain (MCMC) algorithms for parameter estimation. A simulation study was performed in order to evaluate parameter recovery for the proposed model and the selected algorithm concerning convergence issues. Results reveal that the proposed algorithm recovers properly all model parameters. Furthermore, we analyzed a real data set which presents asymmetry concerning the latent traits distribution. The results obtained by using our approach confirmed the presence of negative asymmetry for some latent trait distributions.
Very often, in psychometric research, as in educational assessment, it is necessary to analyze item response from clustered respondents. The multiple group item response theory (IRT) model proposed by Bock and Zimowski [12] provides a useful framework for
Subject: Teoria da resposta ao item
Distribuição normal assimétrica
Inferência bayesiana
Métodos MCMC (Estatística)
Country: Reino Unido
Editor: Taylor & Francis
Citation: Journal Of Applied Statistics. Taylor & Francis Ltd, v. 40, n. 10, n. 2129, n. 2149, 2013.
Rights: Fechado
Identifier DOI: 10.1080/02664763.2013.807331
Address: https://www.tandfonline.com/doi/full/10.1080/02664763.2013.807331
Date Issue: 2013
Appears in Collections:IMECC - Artigos e Outros Documentos

Files in This Item:
File SizeFormat 
000324367400003.pdf674.56 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.