I am running a path model that is essentially an APIM model of infant-mother dyads. In the model I want to test the interaction of an exogenous variable (mother attachment status) on infant affect in predicting mother behavior. I am able to create the continuous interactions using the DEFINE command but I have a few questions:
1) When I grand mean center the interaction variables either in Mplus by:
or by creating them externally in SPSS before saving my input file, the overall test of model fit and the main effects estimates for the interaction variables are different than what they were in the raw (uncentered) model. Interestingly, the interaction effects are identical. Why is this?
2)I have searched high and low but have not found an adequate explanation of how to probe the interaction. Is there a resource I can be pointed to?
In running my continuous path interaction analyses (all variables involved in the interaction centered) the model converges but I get the warning message re: the SE's being untrustworthy due to....a possible linear dependency. Tech 1 gives me the problematic parameter and it indeed is one of the interaction terms. Given that such a term is likely to be a linear dependency on its constituents, how problematic is this warning in the context of a model with interaction terms?
Tracy Witte posted on Wednesday, March 20, 2013 - 6:19 am
I have a question about centered variables in Mplus. I have created the centered terms in SPSS and want to use them in a path analysis with an interaction term. Since there is missing data, and Mplus uses FIML to handle it, I've noticed that the means for the centered variables differ from 0. Given this, I'm concerned that this will affect interpretation, should I find a significant interaction. Is anyone aware of guidelines regarding how to deal with centered variables when using FIML to handle missing data?