Hello everyone,

I'm using the user-written KHB command in Stata to conduct mediation analyses using a binary DV, continuous IV, and three continuous mediator variables. The code works; however, I'm having a bit of trouble understanding the "components of difference" table. Here are my specific questions:

1. I understand that in the components of difference table, the total indirect effect is being decomposed, and, as you can see, one coefficient is positive, the others are negative. I'm assuming the negative coefficient and the negative "percent reduced" is indicating a suppressor effect of mastery_std (if this is wrong, please tell me)? If I am correct, what exactly does this mean?

2. How do I determine whether the mediating or suppressor effect for each individual mediator is statistically significant? Is there something that I can put into the code that will spit out a p-value, conf.interval, etc?

3. In the paper I'm writing, I discuss the contribution of each individual mediator for the indirect effect, which I can get from the components of difference table; however, because there seems to be a suppressor effect of mastery_std, reporting the "percent reduced" of the other two mediators (i.e., stress_std and esteem_std) would be incorrect because they add up to over 100%. So, for example, in the paper, it wouldn't make sense to write something like, "...When broken down by individual mediator, esteem_std and stress_std account for 18% and 86% of the association between X and Y, respectively." To determine the contribution of each individual mediator in this case, should I just examine each mediator individually and treat the other mediators as control variables?

Thank so much for your help!

My code:

khb logit anxiety discrimination_std || c.esteem_std mastery_std stress_std ///
[pw=WGTCENT] if caribbean==1, concomitant(i.female c.age_15 ///
c.income_3 i.nativity) summary disentangle or Array