Estimating Difficulty from Polytomous Categorical Data

被引:7
|
作者
Revuelta, Javier [1 ]
机构
[1] Univ Autonoma Madrid, Dept Social Psychol & Methodol, E-28049 Madrid, Spain
关键词
nested effects parameterization; nominal categories model; generalized logit-linear item response model; identifiability; polytomous item response theory; MAXIMUM-LIKELIHOOD ESTIMATION; ITEM RESPONSE MODEL; MULTIPLE-CHOICE; PARAMETERS; MATRICES; ABILITY;
D O I
10.1007/s11336-009-9145-9
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
A comprehensive analysis of difficulty for multiple-choice items requires information at different levels: the test, the items, and the alternatives. This paper introduces a new parameterization of the nominal categories model (NCM) for analyzing difficulty at these three levels. The new parameterization is referred to as the NE-NCM and is statistically equivalent to the NCM. The NE-NCM is applied to a sample of responses from a logical analysis test. The results suggest that the individuals execute a self-terminated response process that is mostly determined by working memory load.
引用
收藏
页码:331 / 350
页数:20
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