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Bjorner, J. B., Kosinski, M., & Ware, J. E., J.. (2003). Calibration of an item pool for assessing the burden of headaches: an application of item response theory to the Headache Impact Test (HIT). Quality of Life Research, 12, 913-933.

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Wang, C., Chen, P., & Jiang, S.. (2020). Item Calibration Methods With Multiple Subscale Multistage Testing. Journal of Educational Measurement, 57, 3-28. doi:10.1111/jedm.12241

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Bjorner, J. B., Kosinski, M., & Ware, J. E., J.. (2003). Calibration of an item pool for assessing the burden of headaches: an application of item response theory to the Headache Impact Test (HIT). Quality of Life Research, 12, 913-933.

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Raiche, G., & Blais, J. G.. (2009). Considerations about expected a posteriori estimation in adaptive testing: adaptive a priori, adaptive correction for bias, and adaptive integration interval. Journal of Applied Measurement, 10, 138-56.

Cheng, Y., & Chang, H. - H.. (2009). The maximum priority index method for severely constrained item selection in computerized adaptive testing. British Journal of Mathematical and Statistical Psychology, 62, 369-83. presented at the May.

Panter, A. T., & Reeve, B. B.. (2002). Assessing tobacco beliefs among youth using item response theory models. Drug and Alcohol Dependence, 68, S21-S39. presented at the Nov.

Chen, S. - Y., & Doong, S. H.. (2008). Predicting item exposure parameters in computerized adaptive testing. British Journal of Mathematical and Statistical Psychology, 61, 75-91. presented at the May.

Riley, B. B., & Carle, A. C.. (2011). Detecting DIF between Conventional and Computerized Adaptive Testing: A Monte Carlo Study. In Annual Conference of the International Association for Computerized Adaptive Testing. presented at the 10/2011.

Andres, P. L., Black-Schaffer, R. M., Ni, P., & Haley, S. M.. (2004). Computer adaptive testing: a strategy for monitoring stroke rehabilitation across settings. Stroke Rehabilitation, 11, 33-39. presented at the Spring.

Riley, B. B., & Carle, A. C.. (2012). Comparison of two Bayesian methods to detect mode effects between paper-based and computerized adaptive assessments: a preliminary Monte Carlo study. BMC Med Res Methodol, 12, 124. presented at the 2012. doi:10.1186/1471-2288-12-124

Riley, B. B., & Carle, A. C.. (2011). Detecting DIF between Conventional and Computerized Adaptive Testing: A Monte Carlo Study. In Annual Conference of the International Association for Computerized Adaptive Testing. presented at the 10/2011.

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Hol, A. M., Vorst, H. C. M., & Mellenbergh, G. J.. (2007). Computerized adaptive testing for polytomous motivation items: Administration mode effects and a comparison with short forms. Applied Psychological Measurement, 31, 412-429.

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Verschoor, A., Radtke, I., & Eggen, T.. (2011). A Test Assembly Model for MST. In Annual Conference of the International Association for Computerized Adaptive Testing. presented at the 10/2011.

Lee, S. (2017). An Empirical Simulation Study Using mstR for MST Designs. In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University.

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Straat, H., van Groen, M., Zijlstra, W., Keizer-Mittelhaëuser, M. - A., & Lamoré, M.. (2017). Multi-stage Testing for a Multi-disciplined End-of primary-school Test . In IACAT 2017 Conference. presented at the 08/2017, Niigata, Japan: Niigata Seiryo University. Retrieved from https://drive.google.com/open?id=1C5ys178p_Wl9eemQuIsI56IxDTck2z8P

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Wang, C., Chen, P., & Jiang, S.. (2020). Item Calibration Methods With Multiple Subscale Multistage Testing. Journal of Educational Measurement, 57, 3-28. doi:10.1111/jedm.12241