Message/Author |
|
JMC posted on Tuesday, March 19, 2013 - 11:44 am
|
|
|
Hi Drs. Muthen, Thanks in advance for your help. I am interested in including an index of factor validity, such as Coefficient H. I didn't see any mention of this in the manual. Can offer some guidance? Thank you. |
|
|
I am not familiar with Coefficient H. Mplus does not compute this as an option. |
|
JMC posted on Wednesday, March 20, 2013 - 1:26 pm
|
|
|
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 again for your time. |
|
|
1. Mplus has no option for this coefficient. 2. You can use TYPE=MIXTURE. CLASSES = c (1); 3. There is no outlier detection for count variables. |
|
JMC posted on Sunday, March 31, 2013 - 12:30 am
|
|
|
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; OUTPUT: SAMP STAND RES; Thank you for your help! |
|
|
In the VARIABLE command add CLASSES = c (1); In the MODEL command before the BY statements add %OVERALL% In the ANALYSIS command add TYPE=MIXTURE; Regarding non-convergence, send the output and your license number to support@statmodel.com. |
|
Back to top |