R - moderated mediation using the lavaan package I am interested in determining the conditional indirect effects of X on Y at a series of values for a third variable Z.  
I was able to use the lavaan package to calculate some initial indirect effects based of the syntax available in this post: Multiple mediation analysis in R
However, I do not know how to access an output of values for conditional indirect effects once I add the interaction term into the equation.
Any support or suggestions for other packages to use would be greatly appreciated.
 A: I posted this question in another location and was provided the answer by Terry Jorgenson.  Question and answer:
I would like to calculate the conditional indirect effects of X on Y given a set of values for the moderator W.  Both X and the moderator are continuous.  Could you provide some direction for structuring the model syntax?
Assuming X and W are both observed variables, you can calculate the product term XW in your data.frame and simply add the product term (X-W interaction) to the models for M and Y in Yves' example earlier in this thread (but a single-group version, since your moderator is continuous).
model <- ' 
  Y ~ c*X + cw*XW + b*M
  M ~ a*X + aw*XW
  ## indirect and total effects, conditional on W == 0
  ab0 := a*b            # + 0*aw*b
  total0 := ab0 + c     # + 0*cw
  ## indirect and total effects, conditional on W == 1
  ab1 := ab0 + 1*aw*b
  total1 := ab1 + c + 1*cw
  ## indirect and total effects, conditional on W == 2
  ab2 := ab0 + 2*aw*b
  total2 := ab2 + c + 2*cw
'

This is specifically designed to assess conditional indirect effects using the lavaan package.
