Abstract
Gaussian kernel continuization of the score distributions has been the standard choice in kernel equating. In this paper we illustrate the use of both the Epanechnikov and adaptive kernels in the actual equating step using the R package SNSequate (González, J Stat Softw 59(7):1–30, 2014). The two new kernel equating methods are compared with each other and with the Gaussian, logistic, and uniform kernels.
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Acknowledgements
The first author acknowledges partial support of grant Fondecyt 1150233. The authors thank Ms. Laura Frisby, ACT, for editorial help.
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González, J., von Davier, A.A. (2017). An Illustration of the Epanechnikov and Adaptive Continuization Methods in Kernel Equating. In: van der Ark, L.A., Wiberg, M., Culpepper, S.A., Douglas, J.A., Wang, WC. (eds) Quantitative Psychology. IMPS 2016. Springer Proceedings in Mathematics & Statistics, vol 196. Springer, Cham. https://doi.org/10.1007/978-3-319-56294-0_23
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DOI: https://doi.org/10.1007/978-3-319-56294-0_23
Publisher Name: Springer, Cham
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