I have a model with a one predictor, one mediator and one outcome. The following are the coefficients i got for my mediation analysis, but I can't understand how to make sense of them. Could someone please help explain what must be going on and how I can report these results.

The indirect effect is significant (b = 0.041, CI [0.0103 and 0.0781]) The Total effect is non-significant ((b = 0.016, t = 0.323, p=0.747) The direct effect is non-significant with a flipped sign for the coefficient,( -0.03, p=0.619)

is it valid to conduct a mediation in this scenario? how do I report my results.

P.S; I ran my analysis with Hayes PROCESS macro P.P.s; I would really appreciate if someone could help soon because I'm on a bit of a time crunch.


1 Answer 1


The total effect is the sum of the direct and indirect paths. There is no conflict, as this is indeed the case in your example. You have evidence to claim the indirect effect is different from 0. You can't say much about the total or direct effects because they are nonsignificant. Nonsignificant doesn't mean equal to 0. It means if there were equal to 0, you would see results like the ones you saw often. Your results are compatible with the following patterns:

  • A positive indirect effect, a negative direct effect, and 0 total effect, indicating two compensatory paths (e.g., in a system designed for stability, where one path offsets the other to minimize the total effect of the main predictor)
  • A positive indirect effect, a 0 direct effect, and a positive total effect, indicating full mediation by the mediator
  • A positive indirect effect, a positive direct effect, and a positive total effect, indicating partial mediation by the mediator

There may be other combinations as well. The point is that you cannot distinguish among them from your data. You may say, "my direct effect was negative, so how does the third option make sense?" The direct effect was negative in your sample, but the confidence interval for the direct effect (which you did not display) contains positive values, meaning the true direct effect could be positive. Again, you simply don't have enough information to determine that, but that doesn't mean there is any conflict in your results.


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