Tree-Based Global Model Tests for Polytomous Rasch Models

Autor/inn/en	Komboz, Basil; Strobl, Carolin; Zeileis, Achim
Titel	Tree-Based Global Model Tests for Polytomous Rasch Models
Quelle	In: Educational and Psychological Measurement, 78 (2018) 1, S.128-166 (39 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164416664394
Schlagwörter	Item Response Theory; Models; Tests; Measurement; Statistical Analysis; Comparative Analysis; Test Bias; Measures (Individuals); Computation + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Analogiemodell; Examination; Prüfung; Examen; Messverfahren; Statistische Analyse; Testkritik; Messdaten
Abstract	Psychometric measurement models are only valid if measurement invariance holds between test takers of different groups. Global model tests, such as the well-established likelihood ratio (LR) test, are sensitive to violations of measurement invariance, such as differential item functioning and differential step functioning. However, these traditional approaches are only applicable when comparing previously specified reference and focal groups, such as males and females. Here, we propose a new framework for global model tests for polytomous Rasch models based on a model-based recursive partitioning algorithm. With this approach, a priori specification of reference and focal groups is no longer necessary, because they are automatically detected in a data-driven way. The statistical background of the new framework is introduced along with an instructive example. A series of simulation studies illustrates and compares its statistical properties to the well-established LR test. While both the LR test and the new framework are sensitive to differential item functioning and differential step functioning and respect a given significance level regardless of true differences in the ability distributions, the new data-driven approach is more powerful when the group structure is not known a priori--as will usually be the case in practical applications. The usage and interpretation of the new method are illustrated in an empirical application example. A software implementation is freely available in the R system for statistical computing. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01