The Rise of Markov Chain Monte Carlo Estimation for Psychometric Modeling. (8th December 2009)

• Record Type: Journal Article
• Authors: Levy, Roy
• Other Names: van der Heijden Peter Academic Editor.
• Is Part Of: Journal of probability and statistics. Volume 2009(2009)
• Publication Date: 2009-12-08
• Subjects: Probabilities -- Periodicals; Mathematical statistics -- Periodicals; Mathematical statistics; Probabilities; Periodicals; 519
• DOI: 10.1155/2009/537139
• Languages: English
• ISSNs: 1687-952X

Abstract

Abstract : Markov chain Monte Carlo (MCMC) estimation strategies represent a powerful approach to estimation in psychometric models. Popular MCMC samplers and their alignment with Bayesian approaches to modeling are discussed. Key historical and current developments of MCMC are surveyed, emphasizing how MCMC allows the researcher to overcome the limitations of other estimation paradigms, facilitates the estimation of models that might otherwise be intractable, and frees the researcher from certain possible misconceptions about the models.