SF Wang posted on Tuesday, October 08, 2013 - 12:26 pm
The standard 3-step approach is (1)GMM w/o covariates; (2) get class assignment; (3) further analysis, usually logistic regression. Actually to M+ users, steps (1) and (2) are done in one step - one GMM fit provides the class assignments as an output data.
Now standard 3-step approach is replaced by a new 3-step approach by adding "Auxiliary = (R3STEP) x;" statement.
But after reading the webnotes, I am still a little bit confused how many models in M+ we should fit. Please let me know which of the following two understandings is correct: (a)we need to get latent class membership from a GMM w/o covariates and get the error probabilities too, and then feed these into another GMM (with the auxiliary statement) and get the correct class assignment? (b)we only need to replace step (1) in standard 3-step approach by adding auxiliary statement. i.e. the new three steps are: (1)GMM with auxiliary statement; (2) get class assignment; (3) further analysis.
SF Wang posted on Monday, October 21, 2013 - 7:24 am
Thank you for answering my question!
Could you confirm whether my following understandings are correct?
My understanding #1: in the new 3-step approach, auxiliary statement won't change any model results, including the class assignments. It's just logistic regression for class assignment with corrections. Therefore, step(3)-further analysis(logistic regression) has already been done, and the results are in the M-plus output too. (step(2) is done in the same model). So, to users, it's like a one-step procedure.
My understanding #2: if I don't plan to do logistic regressions in step (3)(I am thinking of doing something else, e.g. CART), I wouldn't need the AUXILIARY statement.