期刊
PSYCHOMETRIKA
卷 71, 期 2, 页码 281-301出版社
SPRINGER
DOI: 10.1007/s11336-004-1175-8
关键词
item response theory; marginal maximum likelihood; latent variable; population distribution; density estimation; splines
The purpose of this paper is to introduce a new method for fitting item response theory models with the latent population distribution estimated from the data using splines. A spline-based density estimation system provides a flexible alternative to existing procedures that use a normal distribution, or a different functional form, for the population distribution. A simulation study shows that the new procedure is feasible in practice, and that when the latent distribution is not well approximated as normal, two-parameter logistic (2PL) item parameter estimates and expected a posteriori scores (EAPs) can be improved over what they would be with the normal model. An example with real data compares the new method and the extant empirical histogram approach.
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