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Article

Open Access

Strategies to Measure Direct and Indirect Effects in Multi-mediator Models

Author(s)

Paloma Bernal Turnes, Rircardo Ernst

Full-Text PDF Download XML 2192 Views

DOI:10.17265/1537-1514/2015.10.003

Affiliation(s)

Paloma Bernal Turnes, visiting fellow in Georgetown University, Washington, DC, USA; Rey Juan Carlos University, Madrid, Spain.
Rircardo Ernst, professor in operations and global logistics, Georgetown University, Washington, DC, USA.

ABSTRACT

The analysis of mediators, multi-mediators, confounders, and suppression variables often presents problems to the scientists that need to interpret them correctly. After clarifying main differences among these terms, this paper focuses on the techniques to conduct and estimate multi-mediation effects. Multi-mediator effects are very common in social science literature, however, many studies do not report their analysis, or even worse, do not explore the significance of the indirect effects in the outcome variable. In exploring the underlying mechanism of observed variables, mediation addresses a key important aspect: Mediation explains how the changes occur. The measurement of direct and indirect effects involves the combination of several techniques, especially under multiple mediators. The objective of this paper is to show different approaches that should be used to investigate indirect and direct effects in order to shed some light on how to conduct a mediation analysis, how to assess the model estimation, and how to interpret mediation effects. The main conclusion of this paper is that by applying traditional methodologies (causal steps, product of coefficients, and the indirect approach), the real mediation effect could be overestimated or underestimated. This paper explains new methods that overcome the difficulties of traditional approaches. Examples of Mplus syntax are provided to facilitate the use of these methods in this application.

KEYWORDS

mediator, moderator, cofounder, multi-mediators

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