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Maximum Marginal Likelihood Estimation for Semiparametric Item Analysis
ARTICLE

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Psychometrika Volume 56, Number 3, ISSN 0033-3123

Abstract

A method is presented for estimating the item characteristic curve (ICC) using polynomial regression splines. Estimation of spline ICCs is described by maximizing the marginal likelihood formed by integrating ability over a beta prior distribution. Simulation results compare this approach with the joint estimation of ability and item parameters. (SLD)

Citation

Ramsay, J.O. & Winsberg, S. (1991). Maximum Marginal Likelihood Estimation for Semiparametric Item Analysis. Psychometrika, 56(3), 365. Retrieved October 24, 2019 from .

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