Handling covariate missingness in LPA... PreviousNext
Mplus Discussion > Missing Data Modeling >
 Dylan John posted on Sunday, September 03, 2017 - 11:30 am
I am currently running a 2 timepoint LTA and using the identified transition groups to predict suicidality (dichotomous variable).

When I conducted my LPA I used maximum likelihood estimation to account for missing data, and only included participants that had complete data on at least one indicator variable.

Similarly, I have used full information maximum likelihood estimation in my LTA analysis to account for missingness on my latent profiles at each timepoint.

Where I am seeking guidance is how I should handle (1) my covariates in the LTA, as well as (2) my outcome. For the outcome, I believe I will just remove cases who are missing and then compare them to those who were kept in on sociodemographics and exposures. But, in relation to covariate, what do you recommend I do? Can you account for missingness in covariates using MLE the same way that I did for my latent profiles?
 Bengt O. Muthen posted on Monday, September 04, 2017 - 3:04 pm
The 1-step LTA-covariate analysis can bring the covariates into the model, but their missingness results in dimensions of integration and makes for heavy computations.
 Dylan John posted on Monday, September 04, 2017 - 3:23 pm
How would you suggest I proceed? Would you look to impute the covariates elsewhere and import back into Mplus?
 Bengt O. Muthen posted on Monday, September 04, 2017 - 4:09 pm
It's a difficult situation for which I don't have a good suggestion. Imputation has limited options in any subsequent analysis steps. Bayes is an alternative approach which handles missing on covariates better (see chapter 9 of our RMA book) but Bayes is not always easy to use with mixtures due to label switching (see our Bayes workshop videos).
 Dylan John posted on Wednesday, September 06, 2017 - 2:42 pm
Thanks for your feedback. Would you happen to have any good literature references that describe the issues of missingness in mixture modelling?
 Bengt O. Muthen posted on Wednesday, September 06, 2017 - 4:26 pm
No, I don't. You may want to try SEMNET.
Back to top
Add Your Message Here
Username: Posting Information:
This is a private posting area. Only registered users and moderators may post messages here.
Options: Enable HTML code in message
Automatically activate URLs in message