Peer reviewedERIC Number: EJ590625
Record Type: Journal
Publication Date: 1999
Pages: N/A
Abstractor: N/A
ISBN: N/A
ISSN: ISSN-1076-9986
EISSN: N/A
Available Date: N/A
A Straightforward Approach to Markov Chain Monte Carlo Methods for Item Response Models.
Patz, Richard J.; Junker, Brian W.
Journal of Educational and Behavioral Statistics, v24 n2 p146-78 Sum 1999
Demonstrates Markov chain Monte Carlo (MCMC) techniques that are well-suited to complex models with Item Response Theory (IRT) assumptions. Develops an MCMC methodology that can be routinely implemented to fit normal IRT models, and compares the approach to approaches based on Gibbs sampling. Contains 64 references. (SLD)
Descriptors: Item Response Theory, Markov Processes, Models, Monte Carlo Methods, Research Methodology
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A
