ERIC Number: ED467375
Record Type: Non-Journal
Publication Date: 2001
Reference Count: N/A
A Bayesian Approach to Person Fit Analysis in Item Response Theory Models. Research Report.
Glas, Cees A. W.; Meijer, Rob R.
A Bayesian approach to the evaluation of person fit in item response theory (IRT) models is presented. In a posterior predictive check, the observed value on a discrepancy variable is positioned in its posterior distribution. In a Bayesian framework, a Markov Chain Monte Carlo procedure can be used to generate samples of the posterior distribution of the parameters of interest. These draws can also be used to compute the posterior predictive distribution of the discrepancy variable. The procedure is worked out in detail for the three-parameter normal ogive model, but it is also shown that the procedure can be directly generalized to many other IRT models. Type I error rate and the power against some specific model violations are evaluated using a number of simulation studies. (Contains 8 figures and 55 references.) (Author/SLD)
Descriptors: Bayesian Statistics, Item Response Theory, Markov Processes, Models, Monte Carlo Methods, Simulation
Faculty of Educational Science and Technology, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands.
Publication Type: Reports - Research
Education Level: N/A
Authoring Institution: Twente Univ., Enschede (Netherlands). Faculty of Educational Science and Technology.