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I am working on data of monthly pain assesment among workers. I would like to use the 14 measurements to define classes of workers based on their pain level at each assesment. Therefore LCGA seems to be a way to do so. I am workinig in mplus, but a colleague is using latentgold. We get different results when comparing our analysis. We thought that is was due to the fixed within class variability. Therefore I used the following syntax to free the variance:
ANALYSIS:
TYPE = MIXTURE;
estimator is mlr;
MODEL:
%OVERALL%
i s | INT1@0 INT2@1 INT3@2 INT4@3 INT5@4 INT6@5 INT7@6 INT8@7 INT9@8 INT10@9 INT11@10 INT12@11 INT13@12 INT14@13 ;
%c#1%
i s ;
%c#2%
i s;
%c#3%
i s;
%c#4%
i s ;
Is that correct?
However, we still get different results. My colleague gets a class that contains only 0 all the way (since the data is on a working population, many do not experience pain throughout the year that the Measurements were taken), whereas I get a class with very low pain levels. How can that be? |
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| I would need to see both outputs and your license number at support@statmodel.com to understand the differences. You have freed the variances of i and s. |
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