Non significant VLMR concerns PreviousNext
Mplus Discussion > Growth Modeling of Longitudinal Data >
 Jonathan Codell posted on Monday, March 04, 2013 - 11:24 pm
I am evaluating the trajectory classes of psychological distress in a sample of refugees (n=107) measured across 12 time points.

When extracting trajectory classes BIC, theory, and interpretability point to a 4 or 5 class model. However when applying tech 11 to help determine the ideal number of classes, I am unable to secure a significant VUONG-LO-MENDELL-RUBIN LIKELIHOOD RATIO TEST for any number of classes.

Is this likely due to my relatively small sample size?

If sample size is a limitation for this test, does it still make sense to follow the other indicators listed above? Do you have any suggestions for addressing this issue?

Thank you.
 Linda K. Muthen posted on Tuesday, March 05, 2013 - 6:34 am
This test can have problems. The small sample size may be an issue. Use the information from the other tests and theory.
 Kristin Healey posted on Saturday, March 05, 2016 - 7:01 pm
I am having a similar problem as Jonathan Codell described above in my latent profile analyses. Do you happen to have a citation for such (i.e., VLMR being affected by sample size)? I have found Nylund, Asparouhov, and Muthen (2007), though sample size is not clearly specified as the reason for comparatively poor VLMR performance. Thank you!
 Bengt O. Muthen posted on Sunday, March 06, 2016 - 5:33 pm
If you have problems with VLMR just switch to BIC.
 Nicky O'Reilly posted on Friday, February 10, 2017 - 2:37 pm
Hi there -
I have a somewhat similar question. I previously ran an LCA and the VLMR, LMR, and BLRT were all significant for the 3-class model. I then reran the analysis with the same sample using cluster, strata, and weight. In the weighted analysis, the VLMR and LMR are no longer significant for the 3 class model or 2 model. Other fit indices indicate that the 3 class model makes the most sense. And these outcomes are similar (not the same) as a similar analysis with a different data set. Is it problematic that these change between the weighted and unweighted analysis? Thanks in advance!
 Nicky O'Reilly posted on Friday, February 10, 2017 - 2:54 pm
Sorry - I posted this under the wrong category!
 Bengt O. Muthen posted on Friday, February 10, 2017 - 4:00 pm
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