A Comparison of Two MCMC Algorithms for Estimating the 2PL IRT Models
The fully Bayesian estimation via the use of Markov chain Monte Carlo (MCMC) techniques has become popular for estimating item response theory (IRT) models. The current development of MCMC includes two major algorithms: Gibbs sampling and the No-U-Turn sampler (NUTS). While the former has been used...
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| Format: | Others |
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OpenSIUC
2017
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| Online Access: | https://opensiuc.lib.siu.edu/dissertations/1446 https://opensiuc.lib.siu.edu/cgi/viewcontent.cgi?article=2450&context=dissertations |