Multidimensional ítem response model for nominal variables
EntityUAM. Departamento de Psicología Social y Metodología
10.1177/0146621614536272Applied Psychological Measurement 38.7 (2014): 549-562
ISSN0146-6216 (print); 1552-3497 (online)
Funded byThis article has been supported by Grant PSI2012-31958 from the Spanish Ministry of Economy and Competitiveness (DGICT).
ProjectGobierno de España. PSI2012-31958
SubjectsMultidimensional nominal categories model; Ítem factor analysis; Marginal maximum likelihood; Adaptive GH quadrature; Local independence; Multidimensional item response theory; Psicología
Rights© The Author(s) 2014
This article describes a multidimensional generalization of the nominal categories model that serves to estimate factorial models from nominal and ordinal observed responses, and includes a structural model for latent variables that distinguishes between endogenous and exogenous factors. The model includes a scale parameter for each response category in each factor. Item parameters relate the logit between categories to the vector of latent variables. The inferential framework is marginal maximum likelihood, implemented via static and adaptive Gauss–Hermite quadrature and Monte Carlo EM. The properties of estimators are investigated in a simulation study. An example with real data illustrates the utility of the model in analyzing local dependencies in testlets composed of multiple-choice items that are clustered in several groups around a common theme.
Google Scholar:Revuelta Menéndez, Javier
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