Titlebook: Applying Test Equating Methods; Using R Jorge González,Marie Wiberg Book 2017 The Editor(s) (if applicable) and The Author(s), under exclus

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https://doi.org/10.1007/978-1-349-18098-1describe how to prepare the score distributions in order to read them into the different . packages that will be used. Presmoothingthe score distributions as a first step in equating is also discussed. Known data sets appearing in the equating literature, as well as real data examples from an admiss

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Introduction: Eurocentrism and Racismthe most, although the possibility to use . ?(González, J Stat Softw 59(7):1–30, 2014) for traditional equating methods will also be explored. The methods included in this chapter are mean, linear andequipercentile equating for different data collection designs.

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By Race Jews, by Religion Christiansoftw 59(7):1–30, 2014) and . (Battauz, J Stat Softw 68(7):1–22, 2015) packages. Other useful packages include . (Rizopoulos, J Stat Softw 17(5):1–25, 2006) and . (Chalmers, J Stat Softw, 48(6):1–29, 2012), which allow the user to model response data using different IRT models. IRT objects obtained f

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https://doi.org/10.1007/978-3-030-24929-8 Springer, New York, pp?201–223) can be seen as an attempt to obtain a fairer equating in comparison to the traditional equating methods described in previous chapters. In this chapter, the concept of local equating is presented, and some existing local equating methods that are currently implemente

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