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 NR posted on Monday, June 08, 2009 - 3:30 pm

I'm doing GMM analysis with 5 imputed datasets. When I do the analysis for each imputed dataset separately, I have similar class membership results across 5 imputed datasets. But I run the analysis for all 5 imputed datasets with "type=imputation" option, the class membership results are substantially different from any of the results from a single imputed dataset.
Please let me know how this might happen, and how MPLUS produces combined results for a class membership based on multiply imputed datasets.
Thank you!
 Linda K. Muthen posted on Monday, June 08, 2009 - 4:30 pm
You may have a problem with class switching. Use starting values for the classes so that the order does not change.
 Andrea Howard posted on Wednesday, June 08, 2011 - 12:27 pm
I'm running a 4-class GMM using multiple imputation (20 datasets), and I'm running into some inconsistencies when I save class membership and class probabilities. I've used the procedure I've seen on this discussion board in the past (i.e., set up a model with all values fixed to the parameters from the final model and save data on one of the imputed data sets).

The problem is that the class membership assignments do not correspond perfectly with the classes assigned to cases based on most likely membership across imputed datasets (close, but off by a few cases). I reasoned that this might be a function of saving class probabilities and membership from just a single data set. So, I saved data from all of my imputed data sets and calculated average class probabilities myself -- but these don't match either!!

Now I am questioning how the class assignments are calculated to arrive at the numbers shown in the output. The output reads "CLASSIFICATION OF INDIVIDUALS BASED ON THEIR MOST LIKELY LATENT CLASS MEMBERSHIP", and I assumed this was a function of posterior probabilities across imputations. Am I interpreting this wrong? Is there a way to save class assignment from multiple imputation and get the same classification as printed in the output?

Andrea Howard
 Bengt O. Muthen posted on Thursday, June 09, 2011 - 9:04 am
Please send your files to support so we can diagnose this. You may also be experiencing class switching if you don't use a recent Mplus version.
 Jessica M Hill posted on Monday, June 01, 2015 - 8:03 am

I am running LCA on 5 imputed datasets using 4 categorical variables with 3 levels each. I have also included 3 covariates in the model. After running the model using type=imputation I then fix the parameters to the average estimates and run the analysis again on one single dataset in order to get the class probabilities.
When I do this the classes are different in size to those from the results averaged across the imputed datasets.
My model input looks like this:

[var1$1@-2.071 var1$2@0.530];
[var2$1@-1.381 var2$2@0.322];
[var3$1@-0.089 var3$2@1.207];
[var4$1@-15.000 var4$2@2.204];

[var1$1@-2.456 var1$2@-2.135];
etc. for 4 classes

Am I doing something wrong?

Many thanks, Jessica
 Bengt O. Muthen posted on Monday, June 01, 2015 - 2:34 pm
Please send the two outputs to support along with your license number so we can see the details.
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