Behavior Research Methods

, Volume 40, Issue 3, pp 879–891 | Cite as

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

  • Kristopher J. PreacherEmail author
  • Andrew F. Hayes


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.


Indirect Effect Structural Equation Modeling Residual Covariance Total Indirect Effect Multiple Mediator Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Psychonomic Society, Inc. 2008

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of KansasLawrence
  2. 2.Ohio State UniversityColumbus

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