The Estimates Item Parameter for Multidimensional Three-Parameter Logistics


The purpose of this study is to measure the accuracy of item parameters and abilities by using the Multidimensional Three-Parameter Logistics (M3PL) model. M3PL is a series of tests that measure more than one dimension of ability (θ). Item parameter estimation and the ability to model M3PL are reviewed based on a sample size of 1000 and test lengths of 15, 25, and 40. Parameter estimations are obtained using the Wingen software that is converted to BILOG. The results show that the estimate obtained with a test length of 15 displays a median correlation of 0.787 (high). The study therefore concludes that the level of difficulty of the questions is higher or the questions given to respondents are more difficult, so many respondents guessed the answers. The results of the estimated grain parameters and capabilities indicated that scoring based on sample size greatly affects the stability of the test length. By using the M3PL model, parameters can be measured pseudo-guessing, parameters b and parameters a. MIRT is able to explain interactions between the items on the test and the answers of the participants. The estimated results of the item parameters and the ability parameters of the participants also proved to be accurate and efficient.

Keywords: Multidimensional Three-Parameter Logistics (M3PL), distribution parameter, test length

1] Husen, U. (2011). Research Methods for Thesis and Business. (2nd ed.). Jakarta: PT Raja Grafindo Persada.

[2] Xitao, F. (1998). Book Review of Structural Equation Modeling With LISREL, PRELIS, and SIMPLIS: Basic Consept Applications, and Programming by B.M Byrne. Educational and Psychological Measurement.

[3] Hambleton, R. K., Swaminathan, H. and Rogers, H. J. (1991). Fundamentals of Item Response Theory. CA: Sage Publication Inc.

[4] Yanyan, S. and Wikle, C. K. (2007). Comparing Multidimensional and Unidimensional Item Respon Theory Models. Educational and Phsychological Measurement,

[5] Reckase, M. D. (1997). The Past and Future of Multidimensional Item Respon Theory. Applied Psychological Measurement, doi:10.1177/0146621697211002.

[6] Reckase, M. D. (1985). The Difficulty of Test Items That Measure More Than One Ability. Applied Psychological Measurement.

[7] Samejima, F. (1974). Normal Ogive Model on the Continuous Response Level in the Multidimensional Space. Psychometrika.

[8] Reckase, M. D. (1996). A Linear Logistic Multidimensional Model. In W. J. van der Linder and R. K. Hambleton (Eds.), Handbook of Modern Item Response Theory. New York: Springer-Verlag, pp. 271– 286.

[9] Lord, F. M. (1980). Application of Item Response Theory to Practical Testing Problems. Hillsdale: Lawrence Erlbaum Associates.

[10] Baker, F. B. (2001). The Basic of Item Response Theory. USA: ERIC Clearinghouse on Assessment and Evaluation.

[11] Folk, V. G. and Green, B. F. (1989). Adaptive Estimation when the Unidimensionality Assumption of IRT is Violated. Applied Psychological Measurement.

[12] Yalcin, I. (1995). Nonlinear Factor Analysis. Retrospective Theses and Dissertations. USA: IOWA State University.

[13] McDonald, R. P. (1997). Multidimensional Normal Ogive Model. In W. J. Van der Linden and R. K. Hambleton (Eds.), Handbook of Modern Item Response Theory. New York: Springer-Verlag, pp. 257- 269.

[14] Hambleton, R. K., and Cook, L. L. (1977). Latent Trait Models and their Use in the Analysis of Educational Test Data. Journal of Educational Measurement.

[15] Ackerman, T. A. (1994). Using Multidimensional Item Response Theory to Understand What Items and Tests are Measuring. Applied Measurement in Education.