Maximum marginal likelihood estimation for semiparametric item analysis
作者： J. O. Ramsay , S. Winsberg
DOI: 10.1007/BF02294480
关键词: Polynomial regression 、 Prior probability 、 Differential item functioning 、 Mathematics 、 Marginal likelihood 、 Beta distribution 、 Econometrics 、 Estimation theory 、 Statistics 、 Item analysis 、 Multivariate adaptive regression splines 、 Applied mathematics 、 General psychology
摘要: The item characteristic curve (ICC), defining the relation between ability and probability of choosing a particular option for test item, can be estimated by using polynomial regression splines. These provide more flexible family functions than is given three-parameter logistic family. estimation spline ICCs described maximizing marginal likelihood formed integrating over beta prior distribution. Some simulation results compare this approach with joint parameters.
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