Dear all,

I would like to visualize a latent variable interaction after running sem in Stata 14. To interpret the interaction effect, I would like to plot the effects of the latent predictors on the latent dependent variable for different levels of the moderators (i.e., at 1 SD below and above the mean of the respective moderator). I first thought about using margins in combination with xblatent to get the values for drawing the interaction plot. However, I learnt that using margins in combination with xblatent is not possible.

More detailed illustration: Following Marsh et al. 2004 (please find the reference below), the indicators of the latent interaction term were calculated by multiplying pairs of the (mean-centered) indicators involved in the interaction before running sem. The following code illustrates my model:

Code:
sem (A -> a1 a2 a3 a4) ///
(B -> b1 b2 b3 b4)  ///
(C -> c1 c2 c3 c4) /// mean-centered indicator variables
(D -> d1 d2 d3 d4) /// mean-centered indicator variables
(Interaction_C*D -> ia1 ia2 ia3 ia4) /// The indicators ia1-4 were calculated by multiplying matched pairs of the indicators of C & D before running sem (Marsh et al. 2004)
(E -> f1 f2 f3 f4) ///
(F -> g1 g2 g3 g4) ///
(G -> h1 h2 h3 h4) ///
(C <- A B) ///
(E <- A B C D Interaction_C*D) ///
(F <- A B C D) ///
(G <- E F), cov(e.E*e.F) vce(sbentler) standardized
Referring to the code above, what I would like to do is to visualize the effect of the latent variable interaction on E. Is there a way to get the values for the effects of the latent predictors (C & D) on the latent dependent variable (E) when the moderators are at 1 SD below or above their means?

Reference:
MARSH, Herbert W., WEN, Zhonglin, et HAU, Kit-Tai. Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction. Psychological methods, 2004, vol. 9, no 3, p. 275.