This is a more conceptual question, rather than mathematical per se, so I will talk through an example.
To test the proportion of an effect (outcome ~ exposure) mediated by a variable I have performed 2 linear regression analyses;
- Outcome ~ exposure
- Outcome ~ exposure + mediator
By comparing the coefficients I have determined the proportion of the effect (outcome ~ exposure) mediated by my proposed mediating factor.
If the effect size gets smaller I interpret this as some of the effect of the exposure actually going via the mediator.
My question relates to the occurrences where the effect size gets larger after inclusion of the mediator. I have heard the term "negative mediation", but am having trouble conceptualizing this - how can one have a mediator that does not account for any of the variance between the exposure and the outcome?
Thanks for your time. Ideal answers would keep this simple, as I am not a stats guru - a real world example would be great.