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 Sarah Victor posted on Tuesday, July 31, 2018 - 8:19 am
Hello all,

I am working on a discrete time survival analysis using mixture modeling as per the Muthen & Masyn 2001 paper. My current model appears to be kicking out participants with missing data on any covariate, which I do not want; I would like to bring those variables into the model by estimating their variance.

Here is the syntax:
USEVARIABLES SH14 SH15 SH16 SH17 cov1 cov2;
CLASSES = c(1);
f BY SH14@1 SH15@1 SH16@1 SH17@1;
f ON cov1 cov2;
!cov1 cov2;
f ON cov1 cov2;
!cov1 cov2;

When I try to add the lines commented out above, I get the following error:

One or more MODEL statements were ignored. Note that ON statements must appear in the OVERALL class before they can be modified in class-specific models. Some statements are only supported by ALGORITHM=INTEGRATION.

When I add ALGORITHM=INTEGRATION to the ANALYSIS code, it runs fine. Is this appropriate for use in mixture modeling with discrete time survival analysis?
 Sarah Victor posted on Tuesday, July 31, 2018 - 8:21 am
I am, yet again, sorry about the title - it appears my password manager is entering my username into the title box, and even though I previewed the thread and ensured that the title WAS correctly entered, when I hit "post" following the preview, it changed the title...which should have been "Missing Data in Discrete Time Survival Analysis"
 Bengt O. Muthen posted on Tuesday, July 31, 2018 - 6:01 pm
See UG ex6.19 for a current setup for discrete-time survival, not needing mixtures.

Algo=Int is fine and needed because cov1, cov2 are partially latent variables due to missingness which calls for numerical integration due to categorical outcomes.
 Sarah Victor posted on Wednesday, August 01, 2018 - 7:03 am
Thank you very much!
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