项目反应理论
非参数统计
地方独立性
序数数据
计量经济学
潜变量
独立性(概率论)
集合(抽象数据类型)
计算机科学
单调函数
变量(数学)
罗伊特
测量水平
潜变量模型
多向拉希模型
检验理论
特质
统计
数学
心理测量学
数学分析
程序设计语言
作者
Jean-Benoît Hardouin,Angélique Bonnaud‐Antignac,Véronique Sébille
出处
期刊:Stata Journal
[SAGE Publishing]
日期:2011-03-01
卷期号:11 (1): 30-51
被引量:81
标识
DOI:10.1177/1536867x1101100102
摘要
Item response theory is a set of models and methods allowing for the analysis of binary or ordinal variables (items) that are influenced by a latent variable or latent trait—that is, a variable that cannot be measured directly. The theory was originally developed in educational assessment but has many other applications in clinical research, ecology, psychiatry, and economics. The Mokken scales have been described by Mokken (1971, A Theory and Procedure of Scale Analysis [De Gruyter]). They are composed of items that satisfy the three fundamental assumptions of item response theory: unidimensionality, monotonicity, and local independence. They can be considered nonparametric models in item response theory. Traces of the items and Loevinger's H coefficients are particularly useful indexes for checking whether a set of items constitutes a Mokken scale. However, these indexes are not available in general statistical packages. We introduce Stata commands to compute them. We also describe the options available and provide examples of output.
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