Testing mediation and suppression effects of latent variables - Bootstrapping with structural equation models
Testing mediation and suppression effects of latent variables - Bootstrapping with structural equation models
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DOI：
10.1177/1094428107300343
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发表时间：
2008-04-01
影响因子：
9.5
通讯作者：
Lau, Rebecca S.
中科院分区：
文献类型：
--
作者：
Cheung, Gordon W.;Lau, Rebecca S.
由于中介研究的重要性，研究者们一直在寻找中介效应的最佳统计检验。最常用的方法包括使用零阶和部分相关、层次回归模型和结构方程建模（SEM）的方法。本研究扩展了MacKinnon及其同事（MacKinnon, Lockwood, Hoffmann, West, & Sheets, 2002; MacKinnon, Lockwood, & Williams, 2004; MacKinnon, Warsi, & Dwyer, 1995）的研究成果，通过模拟研究了潜在变量的中介和抑制效应的分布，以及从八种不同方法中得出的置信区间的性质。结果表明，SEM提供了中介和抑制效应的无偏估计，并且偏差校正的自举置信区间在中介和抑制效应的测试中表现最好。介绍了与阿莫斯执行建议程序的步骤。
Because of the importance of mediation studies, researchers have been continuously searching for the best statistical test for mediation effect. The approaches that have been most commonly employed include those that use zero-order and partial correlation, hierarchical regression models, and structural equation modeling (SEM). This study extends MacKinnon and colleagues (MacKinnon, Lockwood, Hoffmann, West, & Sheets, 2002; MacKinnon, Lockwood, & Williams, 2004, MacKinnon, Warsi, & Dwyer, 1995) works by conducting a simulation that examines the distribution of mediation and suppression effects of latent variables with SEM, and the properties of confidence intervals developed from eight different methods. Results show that SEM provides unbiased estimates of mediation and suppression effects, and that the bias-corrected bootstrap confidence intervals perform best in testing for mediation and suppression effects. Steps to implement the recommended procedures with Amos are presented.