Titlebook: Essays on Contemporary Psychometrics; L. Andries van der Ark,Wilco H. M. Emons,Rob R. Me Book 2023 The Editor(s) (if applicable) and The A

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https://doi.org/10.1057/9780230503922d be understood as . with respect to elements of behavior, including item response behavior. In a discussion in the journal ., Sijtsma (.(3), 451–455 (2006)) contrasted this position with the . interpretation of Item Response Theory (IRT) models and the associated theory of validity that I had artic

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Derya ?z?elik Buskermolen,Jacques Terkenest-posttest differences. Besides the traditional sum score-based classical test theory approach, an item level classical test theory approach has been proposed to assess change score reliability. This approach was demonstrated to be superior to the traditional sum score-based approach. However, bot

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https://doi.org/10.1057/9780230362994 are incomplete, the missing data need to be treated prior to carrying out a PCA. Several methods exist for handling missing data prior to carrying out a PCA. The current chapter first discusses the most recent developments regarding the treatment of missing data in PCA. Next, of these methods, the

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Collaborative Practice with Parentse reliability as defined in a classical test theory context as the ratio of true score variance over observed score variance. The factors were the number of items, the level of item discrimination, the number of dimensions, the correlations among dimensions, and the location of the items in relation

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Russell Haines,Nadine Vehring,Malte Kramerlgorithms can be improved when a sample is required from many conditional distributions. Using real-data examples from educational measurement, we show how the algorithms can be used to sample from intractable full-conditional distributions of the person and item parameters in an application of the

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