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Hi, I'm doing a GMM resulting in a 4-class solution. I now want to predict classes (the latent categorical variable) using auxiliary variables by using the 3-step approach (AUXILIARY = var (R3STEP);). My question concerns whether I can obtain odds ratios and confidence intervals for the regression part of the model? And how to do that? Thank you! |
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Neither of this are in the output but you can compute them from the Mplus results. Odss Ratio = EXP(regression parameter estimate) Confidence Limits = regression parameter estimate +- 1.96 * (its standard error) |
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To get the confidence limits for the Odds Ratio just exponentiate the above confidence limits for the regression parameter. |
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Biyao Wang posted on Thursday, December 03, 2015 - 2:05 am
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Dear Tihomir Asparouhov, I'm doing a GMM using 3 wave data and resulted in a 4-class solution. I want to test the relationship between some wave 1 factors and the latent class. The classification was not very high (entropy=0.67) so I want to use the 3 step approach. (1)to test the predictive value of factors, I used R3STEP so the wave 1 factors are used as predictors of latent class. (2)to test the equality of means of factors across latent class, what should I do? Can I use DU3STEP or DE3STEP? What is the difference between them? Can I use wave 1 factors? (in your 2014 paper, you said in DU/DE3STEP variable is distal variable, what is a distal variable? is it the same with distal outcome? does it mean the variable should be assessed at wave 3?) Thank you! |
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(1) you would have to use a manual version of R3STEP to let a factor predict class because R3STEP only allows observed predictors. (2) Use BCH - see the paper on our website: Asparouhov, T. & Muthén, B. (2014). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary second model. Web note 21. This paper has tables at the end describing differences between approaches. I don't think it matters when the auxiliary variable was measured. |
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