Testing Latent Variable Distribution Fit in IRT Using Posterior Residuals

Autor/in	Monroe, Scott
Titel	Testing Latent Variable Distribution Fit in IRT Using Posterior Residuals
Quelle	In: Journal of Educational and Behavioral Statistics, 46 (2021) 3, S.374-398 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998620953764
Schlagwörter	Item Response Theory; Simulation; Scores; Comparative Analysis; Goodness of Fit; Achievement Tests; Foreign Countries; Elementary Secondary Education; Mathematics Tests; Science Tests; Mathematics Achievement; Science Achievement; International Assessment; Grade 12; Test Items; Trends in International Mathematics and Science Study + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Simulation program; Simulationsprogramm; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; Ausland; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; School year 12; 12. Schuljahr; Schuljahr 12; Test content; Testaufgabe
Abstract	This research proposes a new statistic for testing latent variable distribution fit for unidimensional item response theory (IRT) models. If the typical assumption of normality is violated, then item parameter estimates will be biased, and dependent quantities such as IRT score estimates will be adversely affected. The proposed statistic compares the specified latent variable distribution to the sample average of latent variable posterior distributions commonly used in IRT scoring. Formally, the statistic is an instantiation of a generalized residual and is thus asymptotically distributed as standard normal. Also, the statistic naturally complements residual-based item-fit statistics, as both are conditional on the latent trait, and can be presented with graphical plots. In addition, a corresponding unconditional statistic, which controls for multiple comparisons, is proposed. The statistics are evaluated using a simulation study, and empirical analyses are provided. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01