中文体育类核心期刊

中国人文社会科学期刊AMI综合评价(A刊)核心期刊

《中文社会科学引文索引》(CSSCI)来源期刊

美国《剑桥科学文摘》(CSA)收录期刊

中国高校百佳科技期刊

PLS-SEM多变量统计分析在赛事观众研究领域中的应用

Application of PLS-SEM Multivariate Data Analysis on Sports Spectators Research

  • 摘要: 运用文献资料法探讨基于偏最小平方法的结构方程模型(partial least squares structural equation modeling,PLS-SEM)多变量统计分析在当前赛事观众研究领域的应用方法与注意事项。发现:调节变量与中介变量的引入有助于深入理解和分析赛事消费多变量间的影响机理;理解形成性指标与反映性指标的差异对构建赛事消费潜变量测量模型具有重要意义;与基于共变异数的结构方程模型(covariance-based structural equation modeling,CB-SEM)相比,PLS-SEM适用于小样本、非正态分布、多变量复杂模型以及形成性测量模型等多种研究情境。建议:根据赛事消费变量的特点合理选择测量指标;在样本量较小、测量指标包含形成性指标或进行变量间关系的探索性研究中选择使用PLS-SEM。

     

    Abstract: The literature review was used to assess the application of PLS-SEM (partial least squares structural equation modeling) multivariate data analysis on sports spectators.The findings include:Adopting mediating variables and moderating variables is helpful for understanding the relationship between spectator consumption variables. It is important to distinguish the differences between informative variables and reflective variables. Compared with CB-SEM (covariance-based structural equationmodeling), PLS-SEM has the advantages of small sample sizes, non-formal distributions, multiple-variables in complex models and informative measurement models. It is advisable to choose suitable indicators in accordance with latent variables. PLS-SEM is better applied when using small sample sizes, formative indicators included or conducting exploratory research on spectator fields.

     

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