Could you please tell me if it is possible to test an interaction between a latent variable (based on continuous indicators) and an observed variable that is categorical (0 = condition not present, 1= condition present)in SEM? Both the continuous latent variable and observed categorical variable are exogenous (not predicted by other variables). If so what is the best way to go about this? I was thinking I would use the MLR estimator.
Also, do I specify the categorical indicator as categorical in my syntax?
I have a medium sized sample of about 350 participants.
My sample size is 223 and I have a lot of missing data on the two observed binary variables included in the model. I would like to test the effect of an interaction term in the model. The two terms I am using to create the interaction term are hypothesized mediators. Both terms are continuous latent variables measured by ordinal items (5-item likert scales) with 7 and 8 items each. Most items have high kurtosis (the distribution is very pointy and thin in the tails).
Is it appropriate to try to run a model with an interaction term given the small sample size, missing data, and the fact that the items of the continuous latent constructs are not normally distributed?
ANALYSIS: type = random;
MODEL: x BY C1* C2 C3 C4 C5 C6 C7 C8 C9; x@1; stigma BY S1* S2 S3 S4 S5 S6 S7 S8; stigma@1; stigmasw BY sw191* sw192 sw193 sw194 sw195 sw197 sw198; stigmasw@1; stigma ON x; stigmasw ON x; int | stigma XWITH stigmasw; CCU_1 ON x stigma stigmasw; CCU_1 ON int; CCU_2 ON x stigma stigmasw; CCU_2 ON int;