Isaac posted on Thursday, April 14, 2011 - 1:22 pm
Hi, I'm building an LGMM with 4 points. The initial time point has some variability in when the data was collected so I'm trying to decide how to deal with this. The variablility is normally distributed so initially I thought of putting the loading for this time point at the mean. I then thought of using TSCORES but I see that can only be done with TYPE=RANDOM which doesn't allow for classes. Am I right about this. I don't actually think the variability is very meaningful but I'm concerned about doing this correctly. Any advice?
Type=Random Mixture is available with TSCORES and AT. But it can lead to slow computations. Instead, I would investigate the sensitivity to timing by using a multiple cohort, multiple-group approach where you divide the initial time point variability into a few meaningful groups. Then build your model from UG ex6.18.
Isaac posted on Thursday, April 14, 2011 - 3:16 pm
Thanks Bengt, That's EXTREMELY helpful
Isaac posted on Thursday, April 14, 2011 - 5:53 pm
Hi Bengt, I;m getting an error saying that Type=Mixture is not allowed for multiple-group. I'm following ex 6.18. Am I doing something wrong here?