Estimating the following model helped me get the direct effects. This is a set of three models, a beta regression with the final outcome as the dependent variable, and two mediating negative binomial regressions.
However, I'm stuck with calculating the mediation indirect effects, because `gsem` does not support `estat teffects`.
I searched a lot, and finally came across this blog post, but I got frustrated after reading the second paragraph:
The Stats documentation also explains only basic models with normality assumptions and uses `nlcom` to calculate the indirect effects.
Please advise on how to calculate the mediation indirect effects of this model.
Code:
gsem (c.practice_days c.practice_count c.gpa c.gpa#c.practice_days c.gpa#c.practice_count -> final_0_1, family(beta) link(logit)) (1.counting_days 1.counting_days#c.gpa -> practice_days, nbreg) (1.counting_days 1.counting_days#c.gpa practice_days -> practice_count, nbreg), nocapslatent
I searched a lot, and finally came across this blog post, but I got frustrated after reading the second paragraph:
Note that this is a case where all variables are continuous and all models are linear - we are only using `gsem` for its support of svy:, not its support of GLMs. Indirect effects are a more complicated topic in those models which we do not address here.
Please advise on how to calculate the mediation indirect effects of this model.
