Lydia Zhang posted on Thursday, February 01, 2018 - 3:08 pm
I have a quick question about the new 3-step approach for predicting distal outcomes from latent classes. The examples are all about linear regression between latent classes and distal outcomes for the third step.
I am wondering if I can do growth curve modeling for the third step, that is, predicting trajectories over time from latent classes and covariates in Mplus?
We have a 5-class model and 20 multiply imputed data sets. Question: Can we do a manual 3-step approach with multiple imputation? If so, can you point us to the best resource for carrying out this analysis? Many thanks!
Manual 3-step can't be done very well with imputation because the model changes across the data sets. You can switch to BCH, see web note 21, http://statmodel.com/examples/webnotes/webnote21.pdf. That would be easier to do with imputation, similar to User's Guide example 13.13. If you want to do Manual 3-step you can run the 20 sets with the 20 different models separately then combine them manually like in the bottom of page 3 https://www.statmodel.com/download/MI7.pdf If your measurement data is not imputed (is the same across the 20 sets) then you can use the same model in the third step and apply UG 13.13 method with the manual 3-step (but only in this special case when the measurement part is not being imputed).