预测视角下双因子模型与高阶因子模型的一般性模拟比较

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温忠麟¹(

), 汤丹丹¹, 顾红磊²

1华南师范大学心理应用研究中心/心理学院, 广州 510631
2信阳师范学院教育科学学院, 信阳 464000

收稿日期:2018-06-22出版日期:2019-03-25发布日期:2019-01-22
通讯作者:温忠麟E-mail:wenzl@scnu.edu.cn

基金资助:* 国家自然科学基金项目资助(31771245)

A general simulation comparison of the predictive validity between bifactor and high-order factor models

WEN Zhonglin¹(

), TANG Dandan¹, GU Honglei²

1 Center for Studies of Psychological Application / School of Psychology, South China Normal University, Guangzhou 510631, China
2 School of Education Science, Xinyang Normal University, Xinyang 464000, China

Received:2018-06-22Online:2019-03-25Published:2019-01-22
Contact:WEN Zhonglin E-mail:wenzl@scnu.edu.cn

摘要/Abstract

摘要： 高阶因子模型本质上是一种特殊的双因子模型, 应用中却常被当做双因子模型的竞争模型。已有研究以满足比例约束的双因子模型(此时等价于一个高阶因子模型)为真实测量模型产生模拟数据, 比较了用双因子模型和高阶因子模型作为测量模型的预测效果。本文使用不满足比例约束的双因子模型(此时不与任何高阶因子模型等价)为真实测量模型产生模拟数据进行比较, 所得结果与满足比例约束的双因子模型的结果有很大差别, 双因子模型结构系数的相对偏差较小、检验力较高, 但第Ⅰ类错误率略高。结论是, 在比例约束条件成立时可以使用高阶因子模型, 否则, 从统计角度看, 一般情况下使用双因子模型进行预测比较好。

图/表 6

图1双因子模型M1和高阶因子模型M2

图2双因子模型Mb对效标变量的预测

图3高阶因子模型Mh对效标变量的预测

图4不满足比例约束条件时结构系数的相对偏差注：横轴G表示全局因子负荷(下同); 纵轴G-Bias%表示G因子的结构系数的相对偏差; S1-Bias%表示S1因子的结构系数的相对偏差。

图5不满足比例约束条件时结构系数的统计检验力注：G-Power表示G因子的结构系数统计检验力, S1-Power表示S1因子的结构系数统计检验力。

图6不满足比例约束条件时结构系数的第I类错误率注：G-I Error表示G因子的结构系数的第I类错误率, S1-I Error表示S1因子的结构系数的第I类错误率。

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