

10 Timevarying covariates x 9 depend... 

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EFried posted on Friday, March 09, 2012  9:42 am



Hello! I have * 9 dependent variables (9 categorial depressive symptoms, 04), "How do you feel at the moment." * 10 timevarying covariates (life events 110: yes/no), "Did A happen to you within the last 3 months? Did B happen to you within the last 3 months" (etc). * 5 measurement points, time interval 3 months. Both the dependent variables and the timevarying covariates where measured 5 times for each person. My question is whether life events do have a systematic influence on depressive symptoms: do specific life events cause specific patterns of depressive symptoms. (1) Is there any way in MPLUS to calculate ONE interaction test for this, that would conclude: yes, there is some kind of interaction between life events and depressive symptoms. (2) How would I further elaborate this then? E.g. Life Event "1" leads to more depressive symptoms A, B and C, whereas Life Event "2" leads to symptoms B, E and G. Thank you Torvon 


You can do the following where y1, y2, and y3 are repeated measures of y and x1, x1, and x3 are timevarying covariates: y1 ON x1 (1); y2 ON x2 (1); y3 ON x3 (1); 

EFried posted on Monday, March 12, 2012  5:20 am



Linda, thank you. I'm using this code snippet in my GMMs already to include effects of timevarying covariates on my dependent variables. However, what I want to know is whether x1 affects y1, y2, y3 differently than x2 affects y1, y2, y3 (1) How could I do such a thing? (2) And how could I do it with the complications that x is a timevarying covariate, I have 5 measurement points, 10x and 9? Thank you! 

EFried posted on Monday, March 12, 2012  10:13 am



I forgot a "y" there: (2) And how could I do it with the complications that x is a timevarying covariate, I have 5 measurement points, 10x and 9y? 


You would use script like: y1 ON x1 (p10); y1 ON x2 (p11); MODEL TEST: 0 = p10  p11; 

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