[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5351/CKSS.2006.13.3.467

A Refinement on DETECT for Polytomous Test Data

Kim, Hae-Rim (Department of Data Information, Sangji University)

Publication Information

Communications for Statistical Applications and Methods / v.13, no.3, 2006 , pp. 467-477 More about this Journal

Abstract

A multidimensionality detecting procedure DETECT, based on conditional covariances between items, is extended and refined to deal with polytomous item data as well as binary one. A large body of simulation study shows extraordinary performance of DETECT in both enumerating degrees of multidimensionality in a test and discovering dimensionally distinctive item clusters. Real data study also provides very meaningful results, making DETECT a strong dimensionality assessment tool for the test data analysis.

Keywords

DETECT; polytomous; test dimensionality; dimensionally distinctive;

Citations & Related Records

Reference

1	Zhang, J. and Stout, W.F. (1999). The Theoretical DETECT Index of Dimensionality and Its Application To Approximate Simple Structure. Psychometrika, Vol. 64, 213-249 DOI
2	Kim, H.R. (1994). New Techniques for the Dimensionality Assessment of Standardized Test Data. A Doctoral Dissertation, University of Illinois at Urbana-Champaign
3	Kim, H.R. (1997). Dimensionality Structure Analysis in Latent Traits Estimation. Proceedings of Mathematical Education, Vol. 5, 524-532
4	Kim, H.R. (2000a). A Dimensionality Assessment for Polytomously Scored Items Using DETECT. The Korean Communications in Statistics, Vol. 7, 597-603
5	Kim, H.R. (2000b). Some Asymptotic Properties of Conditional Covariance in the Item Response Theory. The Korean Communications in Statistics, Vol. 7, 959-966
6	Masters, G.N. (1982). A Rasch Model for Partial Credit Scoring. Psychometrika, Vol. 47, 149-174 DOI
7	Masters, G.N. and Wright, B.D. (1996). The Partial Credit Model. In W. Linden and R. Hambelton CEdsJ. Handbook of Modem Item Response Theory. New York, NY; Springer
8	Muraki, E. (1992). A Generalized Partial Credit Model: Application of an EM Algorithm. Applied Psychological Measurement, Vol. 16, 159-176 DOI
9	Yu, F. and Nandakumar, R. (2001). Poly-Detect for Quantifying the Degree of Multidimensionality of Item Response Data. Journal of Educational Measurement, Vol. 38, 99- 120 DOI ScienceOn