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How Important is the Choice of Bandwidth in Kernel Equating?

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How Important is the Choice of Bandwidth in Kernel Equating? / Wallin, Gabriel; Häggström, Jenny; Wiberg, Marie.
In: Applied Psychological Measurement, Vol. 45, No. 7-8, 31.10.2021, p. 518-535.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Wallin, G, Häggström, J & Wiberg, M 2021, 'How Important is the Choice of Bandwidth in Kernel Equating?', Applied Psychological Measurement, vol. 45, no. 7-8, pp. 518-535. https://doi.org/10.1177/01466216211040486

APA

Wallin, G., Häggström, J., & Wiberg, M. (2021). How Important is the Choice of Bandwidth in Kernel Equating? Applied Psychological Measurement, 45(7-8), 518-535. https://doi.org/10.1177/01466216211040486

Vancouver

Wallin G, Häggström J, Wiberg M. How Important is the Choice of Bandwidth in Kernel Equating? Applied Psychological Measurement. 2021 Oct 31;45(7-8):518-535. Epub 2021 Oct 20. doi: 10.1177/01466216211040486

Author

Wallin, Gabriel ; Häggström, Jenny ; Wiberg, Marie. / How Important is the Choice of Bandwidth in Kernel Equating?. In: Applied Psychological Measurement. 2021 ; Vol. 45, No. 7-8. pp. 518-535.

Bibtex

@article{376ba192e6f74c9a83ac91f7444304a6,
title = "How Important is the Choice of Bandwidth in Kernel Equating?",
abstract = "Kernel equating uses kernel smoothing techniques to continuize the discrete score distributions when equating test scores from an assessment test. The degree of smoothness of the continuous approximations is determined by the bandwidth. Four bandwidth selection methods are currently available for kernel equating, but no thorough comparison has been made between these methods. The overall aim is to compare these four methods together with two additional methods based on cross-validation in a simulation study. Both equivalent and non-equivalent group designs are used and the number of test takers, test length, and score distributions are all varied. The results show that sample size and test length are important factors for equating accuracy and precision. However, all bandwidth selection methods perform similarly with regards to the mean squared error and the differences in terms of equated scores are small, suggesting that the choice of bandwidth is not critical. The different bandwidth selection methods are also illustrated using real testing data from a college admissions test. Practical implications of the results from the simulation study and the empirical study are discussed.",
author = "Gabriel Wallin and Jenny H{\"a}ggstr{\"o}m and Marie Wiberg",
year = "2021",
month = oct,
day = "31",
doi = "10.1177/01466216211040486",
language = "English",
volume = "45",
pages = "518--535",
journal = "Applied Psychological Measurement",
number = "7-8",

}

RIS

TY - JOUR

T1 - How Important is the Choice of Bandwidth in Kernel Equating?

AU - Wallin, Gabriel

AU - Häggström, Jenny

AU - Wiberg, Marie

PY - 2021/10/31

Y1 - 2021/10/31

N2 - Kernel equating uses kernel smoothing techniques to continuize the discrete score distributions when equating test scores from an assessment test. The degree of smoothness of the continuous approximations is determined by the bandwidth. Four bandwidth selection methods are currently available for kernel equating, but no thorough comparison has been made between these methods. The overall aim is to compare these four methods together with two additional methods based on cross-validation in a simulation study. Both equivalent and non-equivalent group designs are used and the number of test takers, test length, and score distributions are all varied. The results show that sample size and test length are important factors for equating accuracy and precision. However, all bandwidth selection methods perform similarly with regards to the mean squared error and the differences in terms of equated scores are small, suggesting that the choice of bandwidth is not critical. The different bandwidth selection methods are also illustrated using real testing data from a college admissions test. Practical implications of the results from the simulation study and the empirical study are discussed.

AB - Kernel equating uses kernel smoothing techniques to continuize the discrete score distributions when equating test scores from an assessment test. The degree of smoothness of the continuous approximations is determined by the bandwidth. Four bandwidth selection methods are currently available for kernel equating, but no thorough comparison has been made between these methods. The overall aim is to compare these four methods together with two additional methods based on cross-validation in a simulation study. Both equivalent and non-equivalent group designs are used and the number of test takers, test length, and score distributions are all varied. The results show that sample size and test length are important factors for equating accuracy and precision. However, all bandwidth selection methods perform similarly with regards to the mean squared error and the differences in terms of equated scores are small, suggesting that the choice of bandwidth is not critical. The different bandwidth selection methods are also illustrated using real testing data from a college admissions test. Practical implications of the results from the simulation study and the empirical study are discussed.

U2 - 10.1177/01466216211040486

DO - 10.1177/01466216211040486

M3 - Journal article

VL - 45

SP - 518

EP - 535

JO - Applied Psychological Measurement

JF - Applied Psychological Measurement

IS - 7-8

ER -