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用于评估和比较多重中介模型中间接效应的渐近和重抽样策略。

Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.

作者信息

Preacher Kristopher J, Hayes Andrew F

机构信息

Department of Pxychology, University of Kansas, Lawrence, Kansas 66045-7556, USA.

出版信息

Behav Res Methods. 2008 Aug;40(3):879-91. doi: 10.3758/brm.40.3.879.

Abstract

Hypotheses involving mediation are common in the behavioral sciences. Mediation exists when a predictor affects a dependent variable indirectly through at least one intervening variable, or mediator. Methods to assess mediation involving multiple simultaneous mediators have received little attention in the methodological literature despite a clear need. We provide an overview of simple and multiple mediation and explore three approaches that can be used to investigate indirect processes, as well as methods for contrasting two or more mediators within a single model. We present an illustrative example, assessing and contrasting potential mediators of the relationship between the helpfulness of socialization agents and job satisfaction. We also provide SAS and SPSS macros, as well as Mplus and LISREL syntax, to facilitate the use of these methods in applications.

摘要

涉及中介作用的假设在行为科学中很常见。当一个预测变量通过至少一个中间变量(即中介变量)间接影响一个因变量时,中介作用就存在。尽管有明确需求,但评估涉及多个同时存在的中介变量的中介作用的方法在方法学文献中很少受到关注。我们概述了简单中介和多重中介,并探讨了三种可用于研究间接过程的方法,以及在单个模型中对比两个或多个中介变量的方法。我们给出了一个示例,评估并对比社会化代理人的帮助程度与工作满意度之间关系的潜在中介变量。我们还提供了SAS和SPSS宏,以及Mplus和LISREL语法,以方便在应用中使用这些方法。

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