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star09 posted on Wednesday, April 30, 2014 - 4:54 am
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Dear Drs. Can you please advise as to how best to adjust for potential confounding in LCA. I have a covariate that I wish to control for, rather than perform a subsequent sub-group analysis on. Should I add the covariate into the model as a latent class predictor variable? If I can, I think I can proceed with DCAT to see if class membership predicts the distal outcome. Or I have read that I should do a R3STEP and DCAT in two separate steps, but in that case, how do the two steps relate to each other? I don't understand. Thank you. |
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I would include the covariate predicting latent class, but then you can't do DCAT. You can do 3-step "by hand" as in our web note 15. You can also do 1-step with covariate and distal. |
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star09 posted on Thursday, May 01, 2014 - 1:16 am
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Thank you. So do you mean in step 1 of manual 3 step (appendix E) of web note 15, I should include the covariate in the 'usevar' command. Then use the saved data for step 3 (appendix E) to estimate the distal outcome model? In appendix E, which of the variables is the distal outcome? Thank you. |
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Q1. Yes. Q2. Y |
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star09 posted on Thursday, May 01, 2014 - 10:50 pm
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Thank you Dr. Muthen |
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star09 posted on Sunday, May 04, 2014 - 5:56 am
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Can I ask for further clarification please? You advised that would include the covariate predicting latent class, but then one can't do DCAT. I tried doing the above and using DCAT and it did work but will the outputs be incorrect? Variable: Names are CaseID Family SClass SchYr SchLoc Nation wddiday wediday QoL QoLQ4 Sleep SelfCare School Studdich Workdich Housdich Reldich Leisure; Usevariables = CaseID Sleep SelfCare School Studdich Workdich Housdich Reldich Leisure wediday ; Categorical = Studdich Workdich Housdich Reldich wediday ; classes = c(4); AUXILIARY = QoLQ4 (DCAT); Missing are all (-9999) ; IDvariable = CaseID ; Analysis: Type = mixture ; MODEL: %OVERALL% %c#1% [ sleep* ]; [ selfcare* ]; [ school* ]; [ leisure* ]; [ studdich$1* ]; [ workdich$1* ]; [ housdich$1* ]; [ reldich$1* ]; sleep*; selfcare*; school*; leisure*; ... etc Also, you write that I could also do 1-step with covariate and distal. In what circumstances would this be acceptable compared to newer 3 step method? Thank you for your time. |
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I see no covariates in your model. You cannot use DCAT with a covariate and a distal. You can do one-step if the class formation does not change and if your entropy is greater than .8. 3 step is for entropy between .6 and .8. |
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Is there a citation I could use that the one-step is appropriate if the class formation does not change and entropy is greater than .8? |
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The one-step approach is appropriate at any entropy level. If the class formation doesn't change, there is not really an issue in choosing between 1- or 3-step. I don't think there are citations for this. |
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