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The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model

Matthew S Fritz1, David A Kenny2, David P MacKinnon3

  • 1a Department of Educational Psychology , University of Nebraska-Lincoln.

Multivariate Behavioral Research
|October 15, 2016
PubMed

Insights

Violations in mediation analysis, like measurement error or omitted confounders, bias results. These issues can lead to over or underestimation of mediated effects, impacting causal inference validity.

Area of Science:

  • Statistics
  • Psychology
  • Social Sciences

Background:

  • Mediation analysis is crucial for understanding indirect effects in causal inference.
  • Valid causal inferences depend on meeting stringent assumptions in mediation models.
  • Violations of these assumptions can lead to biased parameter estimates for mediated effects.

Purpose of the Study:

  • To examine the individual and combined effects of measurement error and omitted confounders on mediation analysis.
  • To illustrate how these assumption violations impact the estimation of mediated effects using an empirical example.

Main Methods:

  • The study analyzes the single-mediator model.
  • It first examines the impact of measurement error in the mediator, assuming a perfectly reliable independent variable.
  • Subsequently, it investigates the effect of omitting a confounder in the mediator-to-outcome relationship.

Main Results:

  • Measurement error in the mediator tends to underestimate the mediated effect.
  • Omission of a confounding variable tends to overestimate the mediated effect.
  • When both violations co-occur, the mediated effect can be overestimated, underestimated, or rarely, unbiased.

Conclusions:

  • Failure to account for measurement error and omitted confounders significantly biases mediation analysis results.
  • Understanding these combined effects is essential for accurate causal inference.
  • Researchers must carefully consider and address potential assumption violations in their mediation models.
Keywords:
Confoundingmeasurement errormediationsensitivity analysis

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