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Related Experiment Videos

Lower level mediation in multilevel models.

David A Kenny1, Josephine D Korchmaros, Niall Bolger

  • 1Department of Psychology, University of Connecticut, Storrs 06269-1020, USA. kenny@uconnvm.uconn.edu

Psychological Methods
|August 20, 2003
PubMed
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This study introduces a new method for multilevel models with random mediation effects, crucial for analyzing complex hierarchical and repeated measures data accurately.

Area of Science:

  • Statistics
  • Psychology
  • Social Sciences

Background:

  • Multilevel models are essential for analyzing hierarchical and repeated measures data.
  • Existing methods struggle with mediation at lower levels where links vary randomly across upper levels.

Purpose of the Study:

  • To address the limitations in estimating indirect effects in multilevel models with random mediation.
  • To propose a modified approach for calculating indirect effects and their standard errors in such complex models.

Main Methods:

  • Developed an ad hoc method to estimate multilevel models with random mediation effects.
  • Illustrated the method using both real and simulated data for validation.

Main Results:

  • The proposed method modifies formulas for indirect effects and standard errors to account for covariance between random effects.

Related Experiment Videos

  • Demonstrated the applicability and effectiveness of the ad hoc method through data analysis.

    • Conclusions:

    • The developed method provides a viable solution for analyzing complex mediation in multilevel data.
    • Highlights the need for further development towards an ideal method for these advanced statistical models.