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Multiplicative invalidity and its application to complex correlational models.

David Trafimow1

  • 1Department of Psychology, MSC 3452, PO Box 30001, New Mexico State University, Las Cruces, NM 88003-8001, USA. dtrafimo@nmsu.edu

Genetic, Social, and General Psychology Monographs
|November 1, 2007
PubMed
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Social psychologists using complex correlational models risk spurious findings. Even with favorable assumptions, moderately valid measures can create misleading direct and indirect effects in path analyses and structural equation models.

Area of Science:

  • Social Psychology
  • Quantitative Psychology

Background:

  • Complex correlational models (e.g., path analysis, structural equation models) are increasingly used in social psychology to infer causality.
  • Critics highlight issues like model misspecification, inability to infer causality from correlations, and failure to correct for measurement unreliability.

Purpose of the Study:

  • To examine the potential for spurious effects in complex correlational models, even under highly favorable assumptions for modelers.
  • To assess the impact of measurement validity on the integrity of causal inferences derived from these models.

Main Methods:

  • The study employs theoretical analysis, making assumptions maximally favorable to complex correlational modelers by disregarding common criticisms.
  • Focuses on how moderately valid measures can introduce artifactual direct and indirect effects.

Related Experiment Videos

Main Results:

  • Even when common methodological criticisms are disallowed, spurious direct and indirect effects are likely to emerge.
  • The validity of measures is shown to be a critical factor in the reliability of complex correlational analyses.

Conclusions:

  • Social psychologists should exercise caution when employing complex correlational models.
  • Improved handling of measurement validity is essential before widespread adoption of these advanced statistical techniques for causal inference.