The trade-off between accuracy and precision in latent variable models of mediation processes

Alison Ledgerwood, Patrick E. Shrout

Research output: Contribution to journalArticlepeer-review


Social psychologists place high importance on understanding mechanisms and frequently employ mediation analyses to shed light on the process underlying an effect. Such analyses can be conducted with observed variables (e.g., a typical regression approach) or latent variables (e.g., a structural equation modeling approach), and choosing between these methods can be a more complex and consequential decision than researchers often realize. The present article adds to the literature on mediation by examining the relative trade-off between accuracy and precision in latent versus observed variable modeling. Whereas past work has shown that latent variable models tend to produce more accurate estimates, we demonstrate that this increase in accuracy comes at the cost of increased standard errors and reduced power, and examine this relative trade-off both theoretically and empirically in a typical 3-variable mediation model across varying levels of effect size and reliability. We discuss implications for social psychologists seeking to uncover mediating variables and provide 3 practical recommendations for maximizing both accuracy and precision in mediation analyses.

Original languageEnglish (US)
Pages (from-to)1174-1188
Number of pages15
JournalJournal of personality and social psychology
Issue number6
StatePublished - Dec 2011


  • Latent variable
  • Mediation
  • Power
  • Regression
  • Structural equation modeling

ASJC Scopus subject areas

  • Social Psychology
  • Sociology and Political Science


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