I've got a question concerning the degrees of freedom in a twolevel-analysis. I'm conducting a 2-Level-CFA, incorporating 6 variables and two correlated factors on each level. The output indicates that there are 32 free parameters in the model (I agree to that number). With 6 observed continous variables, how many degrees of freedom does the model have (6*7-32=10?)? According to the MPlus-information in the chi-square test of model fit section I should have 16 degrees of freedom. Where do those 6 dfs stem from or where am I wrong?
Thank you for an explanation.
Regards, Florian Fiedler.
bmuthen posted on Wednesday, June 08, 2005 - 7:01 am
You should count the 6 means as well - because you work with multivariate normality, the H1 model has 6 means and 2x21 var-covar parameters.
Sylvie Mrug posted on Thursday, August 02, 2007 - 12:54 pm
I am running a TWOLEVEL model with 3 Level 2 predictors and 1 Level 1 covariate. How can I determine the df for the t-test of each Level 2 predictor? There are 27 Level 2 clusters. Thanks so much for your help.
The ratio of the parameter estimate to the standard error (column three of the output) is a z-score. You can compare it to 1.96 for example.
Sarah Hall posted on Wednesday, December 14, 2011 - 9:30 pm
Hello, I am using TYPE=TWOLEVEL RANDOM to model relationships between 1 individual-level predictor and 2 group-level predictors and a continuous individual-level outcome. I need to report the degrees of freedom for each of the effects, but I notice that these are not provided in the Mplus output. What is the formula for calculating degrees of freedom in a multilevel model such as the one I've described? Thank you! Sarah