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Buchholz, Janine; Hartig, Johannes:

The impact of ignoring the partially compensatory relation between ability dimensions on norm-referenced test scores

In: Psychological Test and Assessment Modeling, 60 (2018) 3 , 369-385

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Document type
3a. Beiträge in begutachteten Zeitschriften; Beitrag in Sonderheft

Schülerleistung, Leistungsmessung, Test, Interpretation, Item-Response-Theory, Modell, Methode, Validität, Mathematische Kompetenz, Sprachfertigkeit, Simulation, Empirische Untersuchung

The IRT models most commonly employed to estimate within-item multidimensionality are compensatory and suggest that some dimensions (e.g., traits or abilities) can make up for a lack in others. However, many assessment frameworks in educational large-scale assessments suggest partially compensatory relations among dimensions. In two Monte-Carlo simulation studies we varied the loading pattern, the latent correlation between dimensions and the ability distribution to evaluate the impact on test scores when a compensatory model is incorrectly applied onto partially compensatory data. Findings imply only negligible effects when true abilities are bivariate normal. Assuming a uniform distribution, however, analyses of differences in test scores demonstrated systematic effects for specific patterns of true ability: High abilities are largely underestimated when the other ability required to solve some of the items was low. These findings highlight the necessity of applying the partially compensatory model under data conditions likely to occur in educational large-scale assessments. (DIPF/Orig.)

Educational Quality and Evaluation