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2018 | OriginalPaper | Buchkapitel

Evaluating Equating Transformations from Different Frameworks

verfasst von : Waldir Leôncio, Marie Wiberg

Erschienen in: Quantitative Psychology

Verlag: Springer International Publishing

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Abstract

Test equating is used to ensure that test scores from different test forms can be used interchangeably. This paper aims to compare the statistical and computational properties from three equating frameworks: item response theory observed-score equating (IRTOSE), kernel equating and kernel IRTOSE. The real data applications suggest that IRT-based frameworks tend to provide more stable and accurate results than kernel equating. Nonetheless, kernel equating can provide satisfactory results if we can find a good model for the data, while also being much faster than the IRT-based frameworks. Our general recommendation is to try all methods and examine how much the equated scores change, always ensuring that the assumptions are met and that a good model for the data can be found.

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Vorheriges Kapitel How to Select the Bandwidth in Kernel Equating—An Evaluation of Five Different Methods

Nächstes Kapitel An Alternative View on the NEAT Design in Test Equating

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Titel: Evaluating Equating Transformations from Different Frameworks
verfasst von: Waldir Leôncio
Marie Wiberg
Verlag: Springer International Publishing
Buch: Quantitative Psychology
Print ISBN: 978-3-319-77248-6

Electronic ISBN: 978-3-319-77249-3

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-77249-3_9

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