An Introduction to the DA-T Gibbs Sampler for the Two-Parameter Logistic (2PL) Model and beyond
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| Title: | An Introduction to the DA-T Gibbs Sampler for the Two-Parameter Logistic (2PL) Model and beyond |
|---|---|
| Language: | English |
| Authors: | Maris, Gunter, Bechger, Timo M. |
| Source: | Psicologica: International Journal of Methodology and Experimental Psychology. 2005 26(2):327-352. |
| Availability: | University of Valencia. Dept. Metodologia, Facultad de Psicologia, Avda. Blasco Ibanez 21, 46010 Valencia, Spain. Tel: +34-96-386-4100; Web site: http://www.uv.es/revispsi/ |
| Peer Reviewed: | Y |
| Page Count: | 26 |
| Publication Date: | 2005 |
| Document Type: | Journal Articles Reports - Descriptive |
| Descriptors: | Bayesian Statistics, Computation, Item Response Theory, Models, Sampling |
| ISSN: | 0211-2159 |
| Abstract: | The DA-T Gibbs sampler is proposed by Maris and Maris (2002) as a Bayesian estimation method for a wide variety of "Item Response Theory (IRT) models". The present paper provides an expository account of the DA-T Gibbs sampler for the 2PL model. However, the scope is not limited to the 2PL model. It is demonstrated how the DA-T Gibbs sampler for the 2PL may be used to build, quite easily, Gibbs samplers for other IRT models. Furthermore, the paper contains a novel, intuitive derivation of the Gibbs sampler and could be read for a graduate course on sampling. (Contains 9 figures and 4 footnotes.) |
| Abstractor: | As Provided |
| Number of References: | 26 |
| Entry Date: | 2009 |
| Accession Number: | EJ844431 |
| Database: | ERIC |
| Abstract: | The DA-T Gibbs sampler is proposed by Maris and Maris (2002) as a Bayesian estimation method for a wide variety of "Item Response Theory (IRT) models". The present paper provides an expository account of the DA-T Gibbs sampler for the 2PL model. However, the scope is not limited to the 2PL model. It is demonstrated how the DA-T Gibbs sampler for the 2PL may be used to build, quite easily, Gibbs samplers for other IRT models. Furthermore, the paper contains a novel, intuitive derivation of the Gibbs sampler and could be read for a graduate course on sampling. (Contains 9 figures and 4 footnotes.) |
|---|---|
| ISSN: | 0211-2159 |
