基于结构方程模型的有调节的中介效应分析

摘要： 有调节的中介模型是中介过程受到调节变量影响的模型。指出了目前有调节的中介效应分析普遍存在的问题：当前有调节的中介效应检验大多使用多元线性回归分析，忽略了测量误差；而基于结构方程模型(SEM)的有调节的中介效应分析需要产生乘积指标，又会面临乘积指标生成和乘积项非正态分布的问题。在简介潜调节结构方程(LMS)方法后，建议使用LMS方法得到偏差校正的bootstrap置信区间来进行基于SEM的有调节的中介效应分析。总结出一个有调节的中介SEM分析流程，并有示例和相应的Mplus程序。文末展望了LMS和有调节的中介模型的发展方向。
Abstract: The analyses of moderated mediation effects are frequently applied to the studies of psychology, education, and other social science disciplines. A moderated mediation model is a combination of both moderation and mediation models. When a mediation effect is moderated by a moderator, the effect is termed moderated mediation and the model is a moderated mediation model. There are three common types of moderated mediation models: first-stage moderated mediation, second-stage moderated mediation, and dual-stage moderated mediation. Researchers have been searching for the most appropriate analytical method for testing moderated mediation. The observed variable regression approach has been the most popular. One critical limitation of regression approach is that regression analyses assume that variables are measured without error, which result in biased estimates of moderated mediation effect. Structural equation modeling (SEM) method has been extensively used to estimate moderated mediation effect because it corrects for measure errors. Product-indicator method was dominantly used to analyze latent moderated mediation model. There are at least two weaknesses frequently found in moderated mediation effects by product-indicator method. First, product-indicator method involve some type of multiplication of indicators to form the indicators of the latent variable that represents the product of the two latent variables, the generation of product indicators make users feel difficult to use. Second, product-indicators are not normal distributed, estimates based on normal assumption may be bias. In order to improve the above shortcomings, the researchers suggest that moderated mediation effects should be analyzed by Latent Moderated Structural Equations method. The purpose of the present study is to summary an effective procedure for analyzing moderated mediation effects based on Latent Moderated Structural Equations. LMS is a distribution analysis. Compared to analyzing moderated mediation by linear regression and product-indicator method, Latent Moderated Structural Equations (LMS) has many advantages. First, LMS uses the raw data of indicator variables directly for estimation and not require the forming of any products of indicator variables. Second, LMS account for the