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Journal Article
DeMars, C. E. (2022). The (non)Impact of Misfitting Items in Computerized Adaptive Testing. Journal of Computerized Adaptive Testing, 9(2). doi:10.7333/2211-0902008
van der Linden, W. J. (1999). Multidimensional adaptive testing with a minimum error-variance criterion. Journal of Educational and Behavioral Statistics, 24, 398-412.
Tseng, F. - L. (2001). Multidimensional adaptive testing using the weighted likelihood estimation. Dissertation Abstracts International Section A: Humanities & Social Sciences, 61, 4746.
PDF icon ga02812.pdf (131.16 KB)
PDF icon ga02812.pdf (131.16 KB)
PDF icon ga02812.pdf (131.16 KB)
Kim, H. - O. (1994). Monte Carlo simulation comparison of two-stage testing and computerized adaptive testing. Dissertation Abstracts International Section A: Humanities & Social Sciences, 54, 2548.
van der Linden, W. J., & Reese, L. M.. (1998). A model for optimal constrained adaptive testing. Applied Psychological Measurement, 22, 259-270.
Barrada, J. R., Olea, J., & Ponsoda, V.. (2007). Methods for restricting maximum exposure rate in computerized adaptative testing. Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 3, 14-23.
PDF icon ba07014.pdf (398.44 KB)
Cella, D., & Nowinski, C. J.. (2002). Measuring quality of life in chronic illness: the functional assessment of chronic illness therapy measurement system. Archives of Physical Medicine and Rehabilitation, 83, S10-7. presented at the Dec.
PDF icon ba06157.pdf (56.69 KB)
van Buuren, N., & Eggen, T. J. H. M.. (2017). Latent-Class-Based Item Selection for Computerized Adaptive Progress Tests. Journal of Computerized Adaptive Testing, 5(2), 22-43. doi:10.7333/1704-0502022
Finkelman, M. D., Weiss, D. J., & Kim-Kang, G.. (2010). Item Selection and Hypothesis Testing for the Adaptive Measurement of Change. Applied Psychological Measurement, 34(4), 238-254. doi:10.1177/0146621609344844
Finkelman, M. D., Weiss, D. J., & Kim-Kang, G.. (2010). Item Selection and Hypothesis Testing for the Adaptive Measurement of Change. Applied Psychological Measurement, 34(4), 238-254. doi:10.1177/0146621609344844
Segall, D. O. (2002). An item response model for characterizing test compromise. Journal of Educational and Behavioral Statistics, 27, 163-179.
Chang, S. - H. (1991). Inter-subtest branching in computerized adaptive testing. Dissertation Abstracts International, 52, 140-141.
Balajthy, E. (2002). Information technology and literacy assessment. Reading and Writing Quarterly, 18, 369-373.
Balajthy, E. (2002). Information technology and literacy assessment. Reading and Writing Quarterly, 18, 369-373.
Reckase, M. D. (2024). The Influence of Computerized Adaptive Testing on Psychometric Theory and Practice. Journal of Computerized Adaptive Testing, 11(1). doi:10.7333/2403-1101001
Grodenchik, D. J. (2002). The implications of the use of non-optimal items in a Computer Adaptive Testing (CAT) environment. Dissertation Abstracts International: Section B: the Sciences & Engineering, 63, 1606.
Barnard, J. J. (2015). Implementing a CAT: The AMC Experience . Journal of Computerized Adaptive Testing, 3(1), 1-12. doi:10.7333/15100301001
PDF icon ICAT- An Adaptive Testing Procedure for the Identification of Idiosyncratic Knowledge Patterns.pdf (322.62 KB)
Tai, M. Him, Cooperman, A. W., DeWeese, J. N., & Weiss, D. J.. (2023). How Do Trait Change Patterns Affect the Performance of Adaptive Measurement of Change?. Journal of Computerized Adaptive Testing, 10(3), 32-58. doi:10.7333/2307-1003032
Reckase, M., Ju, U., & Kim, S.. (2019). How Adaptive Is an Adaptive Test: Are All Adaptive Tests Adaptive?. Journal of Computerized Adaptive Testing, 7(1), 1-14. doi:10.7333/1902-0701001
Almond, R. G., & Mislevy, R. J.. (1999). Graphical models and computerized adaptive testing. Applied Psychological Measurement, 23, 223-37.
Coyle, J. (2001). Final answer?. American School Board Journal, 188, 24-26.

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