

Lagged analysis with zeroinflated co... 

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We've got two variables measured 3 times each. X is a normally distributed and Y is a zeroinflated count variable (# of drinks). We are interested in examining the crosslagged relationships between X and Y. I'd like to lag the relationships by one time point only and constrain the relationship to be equal across time. !! Lagged relationships; Y2 ON X1 (a); Y3 ON X2 (a); Y2#1 ON X1 (b); Y3#1 ON X2 (b); X2 ON Y1 (c); X3 ON Y2 (c); This doesn't appear permissible given the fatal error I received: "RECIPROCAL INTERACTION PROBLEM". It seemed like a long shot given the zeroinflation but I wanted to see if it was possible. Thus, I am considering splitting the analysis into two. One for the X predicted by Y and one for Y predicted by X. If you have any other additional suggestions, I'd welcome them. However, my question has to do with what does Mplus do with a zeroinflated count variable that appears on the right hand size of an ON statement. For example, if I do something like this: COUNT ARE Y1Y3 (nbi); Y1Y3 ON gender; Y1#1Y3#1 ON gender; X2 ON Y1 (c); X3 ON Y2 (c); Does Mplus just insert the raw Y1Y6 values as predictors in the regressions? (no distributional assumptions) Thanks! 


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