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anne C posted on Thursday, September 27, 2012 - 6:22 am
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Dear all, I am attempting to run a model using Mplus, to which I am not very familiar. The idea is to compute direct and indirect effect of 4 outcomes (binary) on various predictors using a dataset which has family structure (individual-level are child, nested into 1 parent). I have done this TITLE: SEM attempt with clustered data; DATA: FILE =datos.dat; VARIABLE: NAMES = iid centre num ac1 ac2 ac3 ac4 ap sex agp1 agp2 ; usevariables = iid ac1 ac2 ap agp1 ; missing are all (-9999); CATEGORICAL = ac1 ac2 ap ; CLUSTER is iid; ANALYSIS: TYPE = COMPLEX; MODEL: ac1 ON ap agp1 ; ac2 ON ap agp1 ; ap ON agp1 ; MODEL INDIRECT: ac1 IND agp1; ac2 IND agp1; SAVEDATA: estimates=e:\sem1_estim.dat; The program runs well but I would like to be sure that I am doing the right thing here. Does the structure of the data is well-taken into account with the CLUSTER option? How are the standard-errors computed? Is there a better way to do this? Thank you very much in advance Ane |
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Do the child and parent have the same iid? |
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anne C posted on Friday, September 28, 2012 - 2:05 am
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Dear Linda, The iid identifies the parent, while the child is identified, within the same parent, by the order of birth (num=1 for first child, 2 for second etc). I used the "cluster iid" to take into account the familial structure since in the model, ag1 and ap are variables at parental-level (common for children of the same parent). Thanks for your help Best Ane |
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Then your analysis looks like it is set up correctly. |
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