Thank you so much for getting back to me, this is very helpful. I organized my follow up questions by number for clarity.
1. Coefficient H is a analogous to a Cronbach's alpha for a latent factor. Is there a similar index that Mplus offers so I can report reliability for the latent factor?
2. I want to report my statistical assumptions (normality, linearity, and homoscedasticity) and I know these are available using Tech12 and Tech13, but I am not not using a mixture model. How can I access these values?
3. I would typically report Mahalanobis distance for outliers, but upon reading the manual I learned that this was only available for continuous DVs. I am using a count variable (total number correct) and a categorical variable (grades) for my DVs. What alternative to Mahalanobis would you recommend?
Thank you so much, Dr. Muthen. I spent some time trying to work through this code, but haven't been able to run. The code that you gave me seems to be for a latent class analysis and I don't know how to make that work for my SEM. Can you explain further?
Also, one of my models has a count dependent variable and I cannot get it to converge. It works when I treat as continuous, but not as count. This is my code, can you offer any guidance?
TITLE: ITC SEM CATEGORICAL COUNT DATA: File is C:\Users\cambria\Desktop\imputed_6.txt;
VARIABLE: NAMES ARE ESL IEP ETH FARMS GENDER EFF1-EFF7 COG1-COG12 VAL1-VAL7 GRADES ITC;
USEVAR ARE ETH FARMS GENDER EFF1-EFF7 COG1-COG12 VAL1-VAL7 ITC;
CATEGORICAL IS ETH FARMS GENDER EFF1-EFF7 COG1-COG12 VAL1-VAL7;
COUNT IS ITC;
ANALYSIS: ESTIMATOR = WLS; ITERATIONS = 10000;
MODEL: EFF BY EFF1-EFF7; COG BY COG1-COG12; VAL BY VAL1-VAL7;
ITC ON VAL (a1); ITC ON EFF (a2); ITC ON COG (a3); ITC ON FARMS( a4); ITC ON ETH (a5); ITC ON GENDER (a8); COG ON VAL (a6); COG ON EFF (a7);
MODEL CONSTRAINT: NEW (VALMED EFFMED MEDTOTAL); VALMED = A6*A3; EFFMED = A7*A3; MEDTOTAL = VALMED + EFFMED;