Bayesian Estimation of MIRT Models with General and Specific Latent Traits inMATLAB
Author(s) -
Yanyan Sheng
Publication year - 2010
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v034.i03
Subject(s) - markov chain monte carlo , computer science , bayesian probability , software , gibbs sampling , matlab , latent variable , software package , convergence (economics) , data mining , machine learning , artificial intelligence , programming language , economics , economic growth
Multidimensional item response models have been developed to incorporate a general trait and several specific trait dimensions. Depending on the structure of these latent traits, different models can be considered. This paper provides the requisite information and description of software that implement the Gibbs sampling procedures for three such models with a normal ogive form. The software developed is written in the MATLAB package IRTm2noHA. The package is flexible enough to allow a user the choice to simulate binary response data with a latent structure involving general and specific traits, specify prior distributions for model parameters, check convergence of the MCMC chain, and obtain Bayesian fit statistics. Illustrative examples are provided to demonstrate and validate the use of the software package.
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