Abstract
In this chapter, we describe the R package catR that contains most CAT options and routines currently developed. Its general architecture is presented and most important R functions are explained and illustrated. Focus is put on detailing the input arguments and output values of the main functions, as well as the relationships between them and their accurate use in adaptive and non-adaptive contexts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barrada, J. R., Abad, F. J., & Veldkamp, B. P. (2009). Comparison of methods for controlling maximum exposure rates in computerized adaptive testing. Psicothema, 21, 313–320.
Barrada, J. R., Olea, J., Ponsoda, V., & Abad, F. J. (2008). Incorporating randomness to the fisher information for improving item exposure control in cats. British Journal of Mathematical and Statistical Psychology, 61, 493–513. https://doi.org/10.1348/000711007X230937
Barrada, J. R., Olea, J., Ponsoda, V., & Abad, F. J. (2010). A method for the comparison of item selection rules in computerized adaptive testing. Applied Psychological Measurement, 34, 438–452. https://doi.org/10.1177/0146621610370152
Bradlow, E. T. (1996). Negative information and the three-parameter logistic model. Journal of Educational and Behavioral Statistics, 21, 179–185. https://doi.org/10.2307/1165216
Dodd, B. G., De Ayala, R. J., & Koch, W. R. (1995). Computerized adaptive testing with polytomous items. Applied Psychological Measurement, 19, 5–22. https://doi.org/10.1177/014662169501900103
Jeffreys, H. (1939). Theory of probability. Oxford, UK: Oxford University Press.
Jeffreys, H. (1946). An invariant form for the prior probability in estimation problems. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, 186, 453–461.
Kingsbury, G. G., & Zara, A. R. (1989). Procedures for selecting items for computerized adaptive tests. Applied Measurement in Education, 2, 359–375. https://doi.org/10.1207/s15324818ame0204\_6
Magis, D. (2013). A note on the item information function of the four-parameter logistic model. Applied Psychological Measurement, 37, 304–315. https://doi.org/10.1177/0146621613475471
Magis, D., & Barrada, J. R. (2017). Computerized adaptive testing with R: Recent updates of the package catR. Journal of Statistical Software, Code Snippets, 76(1), 1–19. https://doi.org/10.18637/jss.v076.c01
Magis, D., & Raîche, G. (2012). Random generation of response patterns under computerized adaptive testing with the R package catR. Journal of Statistical Software, 48(8), 1–31. https://doi.org/10.18637/jss.v048.i08
Revuelta, J., & Ponsoda, V. (1998). A comparison of item exposure control methods in computerized adaptive testing. Journal of Educational Measurement, 35, 311–327. https://doi.org/10.1111/j.1745-3984.1998.tb00541.x
Thompson, N. A. (2009). Item selection in computerized classification testing. Educational and Psychological Measurement, 69, 778–793. https://doi.org/10.1177/0013164408324460
van der Linden, W. J., & Veldkamp, B. P. (2004). Constraining item exposure in computerized adaptive testing with shadow tests. Journal of Educational and Behavioral Statistics, 29, 273–291. https://doi.org/10.3102/10769986029003273
Warm, T. (1989). Weighted likelihood estimation of ability in item response models. Psychometrika, 54, 427–450. https://doi.org/10.1007/BF02294627
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Magis, D., Yan, D., von Davier, A.A. (2017). Simulations of Computerized Adaptive Tests. In: Computerized Adaptive and Multistage Testing with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-69218-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-69218-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69217-3
Online ISBN: 978-3-319-69218-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)