Programming the statistical procedures from SAS

How do I implement three-step modeling with covariates in PROC LCA

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How do I implement three-step modeling with covariates in PROC LCA

I am looking for a little help in implementing Vermunt (2010)'s 3 step approach to latent class modeling with covariates. My model is too complex to incorporate all my covariates in a one step approach so I need to take a "classify-analyze" approach however I do not want to underestimate the effect of the covariates by not correcting for the classification error. 

 

Step 1 - fit LCA model 

Step 2 - assign classes based on posterior probabilities and calculate classification error

Step 3 - fit LCA model with covariates using the assigned class membership as the (only) indicator and treat calculated classification errors as known error probabilities.

 

Does anyone know how to define fixed-value constraints on the model parameters in PROC LCA? The article indicates that I should be treating the calculated classification error (obtained in the second step) as known in the third step.

 

Thanks in advance!

 

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