Identifying Local Dependence with a Score Test Statistic Based on the Bifactor Logistic Model

Autor/inn/en	Liu, Yang; Thissen, David
Titel	Identifying Local Dependence with a Score Test Statistic Based on the Bifactor Logistic Model
Quelle	In: Applied Psychological Measurement, 36 (2012) 8, S.670-688 (19 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621612458174
Schlagwörter	Item Response Theory; Statistical Analysis; Models; Identification; Factor Analysis; Computation; Simulation + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Statistische Analyse; Analogiemodell; Identifikation; Identifizierung; Faktorenanalyse; Simulation program; Simulationsprogramm
Abstract	Local dependence (LD) refers to the violation of the local independence assumption of most item response models. Statistics that indicate LD between a pair of items on a test or questionnaire that is being fitted with an item response model can play a useful diagnostic role in applications of item response theory. In this article, a new score test statistic, S[subscript b], based on the bifactor logistic model is described. To compare the performance of S[subscript b] with the score test statistic (S[subscript t]) based on the threshold shift model, and the LD X[squared] statistic, data were simulated under locally independent, bifactor, and threshold shift conditions. The results summarize the null distributions of all three diagnostic statistics, and their power for various degrees of bifactor and threshold shift LD. Future research directions are discussed, including the straightforward generalization of S[subscript b] for polytomous item response models, and the challenges involved in the corresponding generalizations of S[subscript t] and LD X[squared]. (Contains 8 notes, 3 tables and 9 figures.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10