A MATLAB Package for Markov Chain Monte Carlo with a Multi-Unidimensional IRT Model. Unidimensional item response theory (IRT) models are useful when each item is designed to measure some facet of a unified latent trait. In practical applications, items are not necessarily measuring the same underlying trait, and hence the more general multi-unidimensional model should be considered. This paper provides the requisite information and description of software that implements the Gibbs sampler for such models with two item parameters and a normal ogive form. The software developed is written in the MATLAB package IRTmu2no. The package is flexible enough to allow a user the choice to simulate binary response data with multiple dimensions, set the number of total or burn-in iterations, specify starting values or prior distributions for model
Keywords for this software
References in zbMATH (referenced in 4 articles , 1 standard article )
Showing results 1 to 4 of 4.
- Wu, Jianmin; Bentler, Peter M.: Limited information estimation in binary factor analysis: a review and extension (2013)
- Sheng, Yanyan; Headrick, Todd C.: A Gibbs sampler for the multidimensional item response model (2012)
- Yanyan Sheng: Bayesian Estimation of MIRT Models with General and Specific Latent Traits in MATLAB (2010) not zbMATH
- Yanyan Sheng: A MATLAB Package for Markov Chain Monte Carlo with a Multi-Unidimensional IRT Model (2008) not zbMATH