MAXIMUM MARGINAL LIKELIHOOD ESTIMATION FOR SEMIPARAMETRIC ITEM ANALYSIS

被引：25
|
作者：
RAMSAY, JO
WINSBERG, S
机构：
来源：
PSYCHOMETRIKA | 1991年 / 56卷 / 03期
关键词：
I-SPLINES; MONOTONE SPLINES; REGRESSION SPLINES; BETA-GAUSSIAN QUADRATURE;
D O I：
10.1007/BF02294480
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
The item characteristic curve (ICC), defining the relation between ability and the probability of choosing a particular option for a test item, can be estimated by using polynomial regression splines. These provide a more flexible family of functions than is given by the three-parameter logistic family. The estimation of spline ICCs is described by maximizing the marginal likelihood formed by integrating ability over a beta prior distribution. Some simulation results compare this approach with the joint estimation of ability and item parameters.
引用
收藏
页码：365 / 379
页数：15
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