Correlation matrix in SAMPSTAT output PreviousNext
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 Carolina Schwedhelm posted on Monday, January 22, 2018 - 9:42 am
I am running a two-level model with one latent variable both with effects within and between (outcome variable is continuous). This variable is a dummy variable (4 categories, so I have 3 dummies).

As my latent variable is 0/1, a pearson correlation with the dependent variable would not be possible. So, where does the output of the correlations come from? I cannot reproduce these correlations in SAS or R (neither from the original variables nor from my proc mixed/lmer/stan_glmer multilevel regression outputs) but need to understand where they come from and why they are so different from the other regression outputs.

Thanks a lot for your help!
 Bengt O. Muthen posted on Monday, January 22, 2018 - 10:35 am
Sampstat gives correlations among observed variables (no latents included). It's unclear what your model is. You say
"this variable is a dummy variable" - it sounds like "this" refers to your latent variable, that is, you have a mixture model.
 Carolina Schwedhelm posted on Tuesday, January 23, 2018 - 5:26 am
Hi,

That's right, my dummy variable is my latent variable. This variable actually causes some convergence problems (I'll have to take a look at that too).

My question is, why if it's the same dataset, do I see such different correlations between the observed variables than in SAS and R? I'm having a hard time understanding the calculations behind this output.

Thanks!
 Bengt O. Muthen posted on Tuesday, January 23, 2018 - 3:50 pm
Please send your Mplus output and that of SAS/R (using a pdf) to Support along with your license number.
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