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 August 8, 2024 from https://www.learntechlib.org/p/144906/.

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Keywords

• Ability
• Computer Simulation
• Equations (Mathematics)
• Estimation (Mathematics)
• Graphs
• Item Analysis
• mathematical models
• Maximum Likelihood Statistics
• Regression (Statistics)