Anonymous posted on Monday, May 16, 2005 - 1:14 pm
I am conducting CFA with continuous latent variables using Mplus version 3.1. I am using ML to estimate missing data. I have tested for univariate skewness and kurtosis of the measured indicators using SPSS (without estimating missing data). However, I am unsure how well the results of SPSS tests generalize to the distribution of the data that includes estimates. Is there a way for me to test for skewness and kurtosis within Mplus using ML estimation for missing data?
I am trying to test the multivariate normality for a CFA analysis (23 items, 4 factors). I see from the code above that to do this I should use the mixture option and identify one class. When I do this I get the following error:
TECH11 option is not available for single-class models. Request for TECH11 is ignored.
You have the Base program. You need to Base program and the Mixture add-on.
JOEL WONG posted on Thursday, May 09, 2013 - 1:51 pm
Thanks for responding so quickly.
Based on an old forum post by Bengt, I figured that TECH12 also produces an output to test for multivariate normality.
I could run the output for TECH12 but I am not sure if I understand the output. Do I look at "Observed skewness" and "Observed Kurtosis" to examine multivariate skewness/kurtosis or do these refer to univariate skewness/kurtosis?