Measuring Evidence for Mediation in the Presence of Measurement Error

Journal of Marketing Research, forthcoming

Posted: 2 Jun 2020 Last revised: 13 Jan 2023

See all articles by Arash Laghaie

Arash Laghaie

Nova School of Business and Economics

Thomas Otter

Goethe University Frankfurt - Department of Marketing

Date Written: December 15, 2022

Abstract

Mediation analysis empirically investigates the process underlying the effect of an
experimental manipulation on a dependent variable of interest. In the simplest
mediation setting, the experimental treatment can affect the dependent variable
through the mediator (indirect effect) and/or directly (direct effect). However,
what appears to be an indirect effect in standard mediation analysis may reflect a
data generating process without mediation, including the possibility of a reversed
causal ordering of measured variables, regardless of the statistical properties of the
estimate. To overcome this indeterminacy where possible, we develop the insight
that a statistically reliable total effect combined with strong evidence for conditional
independence of treatment and outcome given the mediator is unequivocal evidence
for mediation as the underlying causal model into an operational procedure. This is
particularly helpful when theory is insufficient to definitely causally order measured
variables, or when the dependent variable is measured before what is believed to
be the mediator. Our procedure combines Bayes factors as principled measures of
the degree of support for conditional independence, with latent variable modeling
to account for measurement error and discretization in a fully Bayesian framework.
Re-analyzing a set of published mediation studies, we illustrate how our approach
facilitates stronger conclusions.

Keywords: mediation, causal model identification, causal direction, measurement, Bayes factor

JEL Classification: C11, C12, C52, M31

Suggested Citation

Laghaie, Arash and Otter, Thomas, Measuring Evidence for Mediation in the Presence of Measurement Error (December 15, 2022). Journal of Marketing Research, forthcoming , Available at SSRN: https://ssrn.com/abstract=3593176 or http://dx.doi.org/10.2139/ssrn.3593176

Arash Laghaie

Nova School of Business and Economics ( email )

Rua da Holanda 1
Carcavelos, 2775-405
Portugal

Thomas Otter (Contact Author)

Goethe University Frankfurt - Department of Marketing ( email )

Frankfurt
Germany
++49.69.798.34646 (Phone)

HOME PAGE: http://www.marketing.uni-frankfurt.de/index.php?id=97?&L=1

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
1,737
PlumX Metrics