I did MIMIC with 7 binary indicators and 2 binary covariates in complex survey with n=1,422. I got significancy result between these two covariates and 2 out of 3 factors, so I want to do Multiple groups (4 groups) analysis to know where the differency from. Since there is no direct effect in my MIMIC model, does it make sence to do Multiple analysis? (because the example in the handout is with direct effect) The other question is how to use "variable" commend for 4 groups? Thank you!
The MIMIC model allows you to test measurement invariance of the intercept parameters. A multiple group analysis allows you to test measurement invariance of other measurement parameters, for example, factor loadings and residual variances.
The VARIABLE command works the same in multiple group analysis as in single group analysis. It names the variables in the data set.
Thanks for your reply! About "model" command, could we use overall model for all groups or we have to specify differences between the overall analysis model in each group(in step 2: fit the model in all groups)? How could we know the specific model would be in each group? Also in the step 2, how could we write "grouping" statement under "variable" commend for four groups? The other question is about the numbers of people in these four groups. They are from size 230-589. Is it large enough? Really appreciate for your help!
Please see Chapter 13 where the use of the overall and group-specific MODEL commands is described as are other issues with multiple group analysis. The GROUPING option works the same no matter how many groups there are. Please see the GROUPING option in the user's guide. The only way to know if a sample is large enough is to do a Monte Carlo study.
Thanks. After reading Chapter 13 in user guild, I still not clear about how to choose which indicator not to be constrained in each specific model because I don't have any direct effect between indicators and covariates in my MIMIC model. Would you please let me know how to deal with this? The other question is about the sample size. Since Monte Carlo can't work on design variables (psu, stratum, etc.) in Mplus, is there any other way to figure out whether the sample size in each group is large enough in Mplus? Thank you!
I am new to MPlus and have a basic question on subgroup analysis. I simply want to run analyses on subsets of data in a single dataset based on some variable attribute. For example, suppose I have a dataset that includes both males and females (in a GENDER variable) and I wanted to run the same analysis on males and females separately. In SAS I would simply include
Dear Dr. Muthen, I have Multilevel-Data and want to do multigroup analysis. I want to do it with a grouping variable on the within level. In my multilevel model I have random slopes which are predicted by between level variables. Using within level variable for grouping brings me an error message. Is it only possible to do the grouping on the between level? Or is there a way to do it with a variable from the within level also?
I am doing multi-group SEM with complex data but I have unequal sample sizes. I was going to use bootstrapping to deal with this however I understand with TYPE=COMPLEX Mplus does not allow this. are there any other commands I can use to deal with unequal sample sizes while doing this type of analysis?