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ERIC Number: EJ911224
Record Type: Journal
Publication Date: 2010-Dec
Pages: 21
Abstractor: As Provided
Reference Count: 36
ISSN: ISSN-1076-9986
Bayesian Estimation of the Logistic Positive Exponent IRT Model
Bolfarine, Heleno; Bazan, Jorge Luis
Journal of Educational and Behavioral Statistics, v35 n6 p693-713 Dec 2010
A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric ICC treats both correct and incorrect answers symmetrically, which results in a logical contradiction in ordering examinees on the ability scale. A data set corresponding to a mathematical test applied in Peruvian public schools is analyzed, where comparisons with other parametric IRT models also are conducted. Several model comparison criteria are discussed and implemented. The main conclusion is that the LPE and RLPE IRT models are easy to implement and seem to provide the best fit to the data set considered. (Contains 4 figures and 2 tables.)
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Publication Type: Journal Articles; Reports - Research
Education Level: Elementary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Peru