Item Response Theory with Estimation of the Latent Density Using Davidian Curves

Autor/inn/en	Woods, Carol M.; Lin, Nan
Titel	Item Response Theory with Estimation of the Latent Density Using Davidian Curves
Quelle	In: Applied Psychological Measurement, 33 (2009) 2, S.102-117 (16 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621608319512
Schlagwörter	Item Response Theory; Personality Measures; Computation; Simulation; Comparative Analysis; Maximum Likelihood Statistics + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Simulation program; Simulationsprogramm
Abstract	Davidian-curve item response theory (DC-IRT) is introduced, evaluated with simulations, and illustrated using data from the Schedule for Nonadaptive and Adaptive Personality Entitlement scale. DC-IRT is a method for fitting unidimensional IRT models with maximum marginal likelihood estimation, in which the latent density is estimated, simultaneously with the item parameters of logistic item response functions, as a Davidian curve. Simulations compare DC-IRT with Ramsay-curve IRT (RC-IRT) and the empirical histogram method (EHM) for a normal, bimodal, or skewed latent distribution. When the latent density was nonnormal, any of the three density estimation methods improved on the normal model. Both DC-IRT and RC-IRT produced more-accurate results than did the EHM. (Contains 3 figures, 3 tables and 3 notes.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10