Siny Tsang posted on Monday, May 11, 2015 - 4:42 pm
We are trying to run a multi-level mediation on some twin data. The mediator (M) and outcome (Y) variables are measured at the individual level (L1), whereas the X variable is measured at the census level (L2).
I was able to set up the model using TYPE = CROSSCLASSIFIED as follows, but we are not quite how to include the twins into the model. I understand that we cannot use multiple grouping with CROSSCLASSIFIED; is there another way to approach this?
%WITHIN% y m; y ON m; %BETWEEN census% x y m; m ON x (a); y ON m (b); y ON x (cp); %BETWEEN twinid% x y m; m ON x (a); y ON m (b); y ON x (cp);
model constraint: new (indirect direct); indirect = a*b; direct = cp;
You can run multiple group by setting up the groups in wide format. For two groups instead of having Y, you would have Y1 and Y2 and the data will have one value and one missing value depending on which group it is in.
You can add MZ/DZ modeling by expressing the ACE components as dependent parameters in model constraints.
I would recommend you drop the path analysis and settle down the univariate model for Y as a first step.
I would also recommend a totally different approach (as a cross verification) where you run a two level model first with census as the cluster variable - estimate the effect of Census (this is the between part of the variable) subtract that from the variable and then proceed with standard twin modeling.
Siny Tsang posted on Sunday, May 17, 2015 - 5:10 pm
Would you mind clarifying the last part of you response? Perhaps I am missing something, wouldn't the "effect" of census be a variance? How do we subtract that out? Or do you mean that we should subtract the census mean from the observations of Y?