I'm looking for assistance in interpreting the outcomes of a Structural Equation Modeling (SEM) analysis that investigated a mediation effect. The analysis showed that both direct paths from the independent variable to the mediator and from the mediator to the dependent variable were significant and negative. However, the indirect effect turned out to be positive and significant. Does this imply that an increase in the independent variable (X) leads to a decrease in the mediator (M), which then, results in an increase in the dependent variable (Y)?
X (PRE)
M (PSR)
Y (SMA)
PRE -> PSR (B = -.20)
PSR -> SMA (B = -.19)
PRE -> PSR -> SMA (B = .04)
The indirect effect is positive because it is, by definition, equal to the product of two (in this case negative) path (regression) coefficients:
Indirect effect = (-.20)*(-.19) = .038.
The 95% confidence interval includes the value of zero though [.00, .09] and therefore, according to the CI, the indirect effect would not be statistically significant at the .05 level.
Any kind of causal interpretation is questionable, especially if you are dealing with non-experimental, cross-sectional data where X is not manipulated and X, M, and Y are measured at the same time point.
See:
Maxwell, S. E., & Cole, D. A. (2007). Bias in cross-sectional analyses of longitudinal mediation. Psychological Methods, 12(1), 23-44.
Maxwell, S. E., Cole, D. A., & Mitchell, M. A. (2011). Bias in cross-sectional analyses of longitudinal mediation: Partial and complete mediation under an autoregressive model. Multivariate Behavioral Research, 46(5), 816-841.
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