Testing multilevel mediation using hierarchical linear models: Problems and solutions

Zhen Zhang, Michael J. Zyphur, Kristopher J. Preacher

Research output: Contribution to journalArticlepeer-review

830 Scopus citations


Testing multilevel mediation using hierarchical linear modeling (HLM) has gained tremendous popularity in recent years. However, potential confounding in multilevel mediation effect estimates can arise in these models when within-group effects differ from between-group effects. This study summarizes three types of HLM-based multilevel mediation models, and then explains that in two types of these models confounding can be produced and erroneous conclusions may be derived when using popularly recommended procedures. A Monte Carlo simulation study illustrates that these procedures can underestimate or overestimate true mediation effects. Recommendations are provided for appropriately testing multilevel mediation and for differentiating within-group versus between-group effects in multilevel settings.

Original languageEnglish (US)
Pages (from-to)695-719
Number of pages25
JournalOrganizational Research Methods
Issue number4
StatePublished - Oct 2009


  • Hierarchical linear models
  • Mediation
  • Multilevel
  • Random coefficient regression

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Strategy and Management
  • Management of Technology and Innovation


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