Journal
APPLIED PSYCHOLOGICAL MEASUREMENT
Volume 33, Issue 2, Pages 102-117Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0146621608319512
Keywords
item response theory; marginal maximum likelihood; latent variable; density estimation; seminonparametric
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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.
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