详细信息
贝叶斯结构方程模型在运动与锻炼心理学中的应用
Application of Bayesian Structural Equation Modeling in Sport and Exercise Psychology
文献类型:期刊文献
中文题名:贝叶斯结构方程模型在运动与锻炼心理学中的应用
英文题名:Application of Bayesian Structural Equation Modeling in Sport and Exercise Psychology
作者:晏宁[1,2];李英[3];李玉磊[1];郭璐[1];毛志雄[1]
第一作者:晏宁
机构:[1]北京体育大学心理学院;[2]北京联合大学心理素质教育中心;[3]北京中法实验学校
第一机构:北京体育大学心理学院,北京100084
年份:2018
卷号:41
期号:9
起止页码:75-82
中文期刊名:北京体育大学学报
外文期刊名:Journal of Beijing Sport University
收录:CSTPCD;;国家哲学社会科学学术期刊数据库;北大核心:【北大核心2017】;社科基金资助期刊;CSSCI:【CSSCI2017_2018】;
语种:中文
中文关键词:贝叶斯方法;结构方程模型;验证性因素分析;交叉载荷;残差相关
外文关键词:Bayesian analysis;structure equation model;confirmatory factor analysis;cross-loading;residual correlation
摘要:目的:旨在介绍贝叶斯结构方程模型的特点及其使用方法。方法:首先讨论了贝叶斯结构方程模型的优势,然后以运动员训练状态检测量表(32×7)的测评数据,分别采用最大似然估计和贝叶斯估计进行二阶验证性因素分析。结果:纳入交叉载荷和残差相关等小方差先验信息的贝叶斯估计模型拟合良好,而采用最大似然估计的模型拟合不理想。分析造成上述差异的原因,并总结贝叶斯结构方程模型的优势和不足。
Purpose: To introduce the characteristics of Bayesian structural equation model and its usage. Methods:Firstly,the advantages of the Bayesian structural equation modeling were discussed in this paper,and then,a second-order confirmatory factor analysis( CFA) was carried out by using maximum likelihood estimation and Bayesian estimation with the data from the Athlete Training State Test Scale( 32 × 7). Results: The Bayesian estimation model incorporating small variance prior information such as cross-load and residual correlation fitted well,but the model fitting using maximum likelihood estimation was not ideal. This study analyzed the reasons for the above differences and summarized the advantages and disadvantages of Bayesian structural equation modeling.
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