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| Isaac posted on Thursday, April 14, 2011 - 7:22 am
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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? |
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| 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. |
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| Isaac posted on Thursday, April 14, 2011 - 9:16 am
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Thanks Bengt,
That's EXTREMELY helpful |
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| Isaac posted on Thursday, April 14, 2011 - 11:53 am
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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? |
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| In mixture multiple-group is handled via KNOWNCLASS (see index). |
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| Xu, Man posted on Thursday, September 14, 2017 - 12:46 am
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Dear Dr. Muthen,
I have a question about TSCORE as well. I have a model with 2 growth curves. The model did not run. Would you pls take a look:
WEIGHT IS cweights;
USEVARIABLES ARE
!zf02m1
dmrraw emrraw fmrraw !variable for first growth curve
ccbmi dcbmi ecbmi fcbmi gcbmi !variables for second curve
cbmiage dbmiage ebmiage fbmiage gbmiage;!measurement time in months (age)
TSCORES = cbmiage dbmiage ebmiage fbmiage gbmiage; ! this was the age in months at the data collection
ANALYSIS:
estimator is mlr;
TYPE = RANDOM;
MODEL:
i_matrix s_matrix | dmrraw@0 emrraw@2 fmrraw@4 AT dbmiage ebmiage fbmiage;
i_bmi s_bmi | ccbmi@0 dcbmi@2 ecbmi@4 fcbmi@6 gcbmi@8
AT cbmiage dbmiage ebmiage fbmiage gbmiage;
i_matrix s_matrix ON i_bmi;
s_bmi with s_matrix;
OUTPUT: STDY STDYX SAMPSTAT;
*** ERROR in MODEL command
The following statement involving | is not correct. The syntax requires a
variable on the left-hand side of the AT keyword.
Problem with: I_BMI S_BMI | AT CBMIAGE DBMIAGE EBMIAGE FBMIAGE GBMIAGE |
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| Jon Heron posted on Thursday, September 14, 2017 - 7:43 am
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Hi Kate
when using tscores and AT the whole command has to be on one line. I think that's the reason for your error. |
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| Xu, Man posted on Thursday, September 14, 2017 - 8:16 am
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Hi Jon,
Thanks! I shortened the variable names but it still seem to have a problem:
USEVARIABLES ARE
!zf02m1
dmrraw emrraw fmrraw
ccbmi dcbmi ecbmi fcbmi gcbmi
c d e f g;
TSCORES = c d e f g;
ANALYSIS:
estimator is mlr;
TYPE = RANDOM;
MODEL:
i_matrix s_matrix | dmrraw@0 emrraw@2 fmrraw@4 AT d e f;
i_bmi s_bmi | ccbmi@0 dcbmi@2 ecbmi@4 fcbmi@6 gcbmi@8 AT c d e f g;
i_matrix s_matrix ON i_bmi;
s_bmi with s_matrix;
OUTPUT: STDY STDYX SAMPSTAT;
*** WARNING in MODEL command
Duplicate AT relationship in definition of random effect:
Y9 X AT D |
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| Jon Heron posted on Thursday, September 14, 2017 - 8:17 am
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| Ahh, can you use two AT commands? |
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| Jon Heron posted on Thursday, September 14, 2017 - 8:23 am
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yes you can as it's done here
http://www.statmodel.com/discussion/messages/14/478.html?1496824847
Not sure what is wrong there, perhaps it's related to the imbalance of the two processes - 3 and 5 time points.
Depending on how varying time is you could just widen your dataset and not use tscores. |
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| Jon Heron posted on Thursday, September 14, 2017 - 8:47 am
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I think I've sussed it - you need a different set of time variables for each line.
If you read the link above (the bit about multiple zeros) that may help |
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