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 Sophia Fikuart posted on Thursday, June 15, 2017 - 10:29 am
Hello Dr. Muthen,

I am running a multilevel model (I compare the Intercept-only-Modell with a Model 1 (Control Variables), a Model 2 (Direct Effects of Predictor Variables) and a Model 3 (Adding Interaction Terms). Some results of Model 3 seem to be weird (a standardized estimate for an interaction term in Model 3 over 1.0 (1.3) and the Chi-Square-Difference Test (comparing Model 3 to Model 2) seems not to be possible because the
-2*LogLikelihood Value of Model 3 is HIGHER than the -2*LogLikelihood Value of Model 2.

Question 1:
Is it possible that the -2*LogLikelihood Value of Model 3 is higher than the one of Model 2, even if the models are nested
(Model 3 includes additionally the interaction terms)?

Question2:
When I look at the correlation between my predictor variables I subsume that there ist multicollinearity between the interaction term (which has this weird estimate)and a predictor.
A there - like in SPSS - any opportunities in Mplus to test for multicollinearity through a Test like VIF or Tolerance?

...As I run the model in Mplus, I am not sure how to transfer the results to SPSS to check for multicollinearity...


Thank you very much.

Kind regards,

Sophia
 Bengt O. Muthen posted on Thursday, June 15, 2017 - 6:00 pm
Q1: No - send to Support along with your license number.

Q2: You can have standardized values greater than 1 if you have more than one predictor. But as you say, this may point to high correlations among the predictors. Perhaps you didn't center the 2 variables going into the interaction. No VIF in Mplus.
 Sophia Fikuart posted on Sunday, June 18, 2017 - 1:48 am
Thank you very much!

I send it to support. How long does it approximately take to get an answer from your support team?

Thanks.

Sophia
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