心理学报2025，Vol.57Issue(5)：915-928,后插1-后插6,20.DOI:10.3724/SP.J.1041.2025.0915
密集追踪数据的有调节的中介效应分析
Moderated mediation analyses of intensive longitudinal data
摘要
Abstract
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,with the following factors taken into account:sample size(N),number of time points(T),indirect effect sizes,and Level-2 variances and covariances.Results show that the estimates for the average mediation effect components(a and b)and the average mediation effect are generally accurate when N≥100 and T≥10.However,a sufficiently large N and T(e.g.,T≥20)are required in order to obtain accurate estimation of Level-2 variances. Lastly,we discuss assumptions and the extensions of ILMM based on DSEM.As usual,the models used in this paper are based on the assumption that the time series is stationary.Otherwise,residual DSEM can be employed to detrend in ILMM analysis.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Key words
intensive longitudinal data/moderated mediation effect/dynamic structural equation model分类
社会科学引用本文复制引用
方杰,温忠麟,王惠惠,顾红磊..密集追踪数据的有调节的中介效应分析[J].心理学报,2025,57(5):915-928,后插1-后插6,20.基金项目
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)和广东省普通高校创新团队项目(2020WCXTD014)资助. （32171091,72074055）
