cacIRT (version 1.0)

cacIRT-package: Classification accuracy and consistency under Item Response Theory

Description

Computes classification accuracy and consistency under Item Response Theory by the approach proposed by Lee, Hanson & Brennen (2002) and Lee (2010) or the approach proposed by Rudner (2001, 2005).

Details

ll{ Package: cacIRT Type: Package Version: 1.0 Date: 2011-09-05 License: GPL (>= 2) LazyLoad: yes } This packages computes classification accuracy and consistency with two recent approaches proposed by Lee, Hanson & Brennan (2002) and Lee (2010) or by Rudner (2001, 2005). The two functions class.Lee() and class.Rud() are the wrapper functions for the respective approaches. They can accept a range of inputs: ability estimates, quadrature points, or response data matrix and item parameters. Marginal indices are computed with either the D or P method (see Lee (2010)).

References

Lee, W. (2010) Classification consistency and accuracy for complex assessments using item response theory. Journal of Educational Measurement, 47, 1--17. Lee, W., Hanson, B. A., & Brennan, R. L. (2002) Estimating consistency and accuracy indices for multiple classifications. Applied Psychological Measurement, 26, 412--432. Lee, W., & Kolen, M. J. (2008) Irt-class: Irt classification consistency and accuracy (version 2.0).

Rudner, L. M. (2001) Computing the expected proportions of misclassified examinees. PracticalAssessment, Research & Evaluation, 7(14), 1--5.

Rudner, L. M. (2005) Expected classification accuracy. Practical Assessment Research & Evaluation, 10(13), 1--4.