密集追踪数据的有调节的中介效应分析  

Moderated mediation analyses of intensive longitudinal data

作　　者：方杰[1] 温忠麟[2] 王惠惠[3] 顾红磊 FANG Jie;WEN Zhonglin;WANG Huihui;GU Honglei(Institute of New Development,Guangdong University of Finance&Economics,Guangzhou 510320,China;Center for Studies of Psychological Application&School of Psychology,South China Normal University,Guangzhou 510631,China;School of Education,Ningxia University,Yinchuan 750021,China;Department of Psychology,School of Educational Sciences,Hunan Normal University,Cognition and Human Behavior Key Laboratory of Hunan Province,Changsha 410081,China)

机构地区：[1]广东财经大学新发展研究院,广州510320 [2]华南师范大学心理应用研究中心/心理学院,广州510631 [3]宁夏大学教育学院,银川750021 [4]湖南师范大学教育科学学院心理系,认知与人类行为湖南省重点实验室,长沙410081

出　　处：《心理学报》2025年第5期915-928,I0021-I0026,共20页Acta Psychologica Sinica

基　　金：国家自然科学基金项目(32171091,72074055);教育部人文社会科学研究规划基金项目(24YJA190003);宁夏回族自治区重点研发计划引才专项(2024BEH04094);广东省普通高校创新团队项目(2020WCXTD014)资助。

摘　　要：密集追踪数据在心理学、管理学等领域的应用日益增多,但密集追踪数据的分析方法研究却比较欠缺。如果将密集追踪数据的有调节的中介效应当成有调节的多水平中介效应进行分析,则忽略了变量之间的历时性关系。本文使用动态结构方程模型建构了被层2变量调节的1-1-1、2-1-1、2-2-1密集追踪中介模型和被层1变量调节的1-1-1密集追踪中介模型。用模拟研究考察了被层2变量调节的1-1-1密集追踪中介模型的参数估计的准确性。接着用示例演示如何进行有调节的密集追踪中介效应分析,并给出相应的Mplus程序。最后,讨论了基于动态结构方程模型的有调节的密集追踪中介模型的前提假设以及模型的拓展。Intensive longitudinal data(ILD)is increasing in fields such as psychology and management,yet research on analytical methods for ILD remains relatively scant.Traditionally,the ILD is statistically modeled as a two-level structure,with Level 1 being the time and Level 2 being individuals.Especially,existing analytical methods treat longitudinal moderated mediation as multilevel moderated mediation,without considering the lagged relationship between variables.A possible solution is to use dynamic structural equation modeling(DSEM)for ILD moderated mediation analysis.DSEM has recently been used for analyzing intensive longitudinal mediation(ILMed;Fang et al.,2024;McNeish&MacKinnon,2022)and intensive longitudinal moderation(ILMod;Speyer et al.,2024).However,it remains unclear how DSEM can be employed in analyzing intensive longitudinal moderated mediation(ILMM).The purpose of this paper is to combine ILMed and ILMod based on DSEM and propose a method of moderated mediation analysis that takes into account the temporal order between variables.For the 1-1-1 ILMed model where all variables are measured at Level 1(i.e.,all variables are ILD),it might be moderated by variables of Level 1 or Level 2.However,for the 2-1-1 ILMed model(i.e.,only the independent variable is measured at Level 2)and the 2-2-1 ILMed model(i.e.,only the dependent variable is measured at Level 1),they could only be moderated by variables of Level 2.Therefore,there are four basic types of ILMM models:2-1-1 ILMed moderated by a level 2 moderator,2-2-1 ILMed moderated by a level 2 moderator,1-1-1 ILMed moderated by a level 2 moderator,and 1-1-1 ILMed moderated by a level 1 moderator.This paper describes in detail how to construct the above four ILMM models with DSEM,so that empirical researchers can understand which kind of ILMM model meets their needs and how to analyze it.Mplus codes for analyzing all these ILMM models are provided.A simulation study is conducted to examine the estimation accuracy of the 1-1-1 ILMed moderated by a level 2 moderator,

关 键 词：密集追踪数据 有调节的中介效应 动态结构方程模型 

分 类 号：B841[哲学宗教—基础心理学]