Shiny App for Bayesian Item Response Theory (SABIRT)

Description

A web interactive application intended for the making of an MCMC (Markov Chain Monte Carlo Methods) estimation and model-fit of the item response models designed by Johnson and Albert (2pno, 1999) and Glas and Beguim (3pno, 2001). The outcome are the items parameters (difficulties and discrimination for 2pno, and additionally the chance to guess the right answers for 3pno) and also the latent abilities of each examinee.

Usage

sabirt()

Author(s)

Javier Martínez and Irene Garcia Mosquera

References

Beguin, A, A. & Glas, C.A.W. (2001). MCMC Estimation and Some Model-Fit Analysis of Multidimensional IRT Models. Psychometrika, 66, 541-562.

Harwell, M. R, & Baker, F. B. (1991). The use of Prior Distributions in Marginalized Bayesian Item Parameter Estimation: A Didactic. Psychometrika, 15, 375-389.

Johnson, V. E. & Albert, J. H. (1999). Ordinal Data Modeling. New York: Springer.