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1-step method in LCA with continous d... |
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Shuai Chen posted on Friday, April 05, 2013 - 10:06 pm
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Hello, I want to do 1-step method in LCA with continous distal outcome x. My model is: x-->c-->y, where c is latent class, y is observed categorical indicator. I want to predict the mean of x from c, ie, E(x|c). How to obtain this from Mplus results? Thank you! Shuai |
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I think you get the x means in each class in the output - request RESIDUAL. |
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Shuai Chen posted on Tuesday, April 09, 2013 - 6:27 pm
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Thank you! One more question, how to obtain E(x|c), if the model changes to be: c-->y? |
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You say that your model is c->y, but what role does x play in the model? |
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Shuai Chen posted on Wednesday, April 10, 2013 - 10:35 pm
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Here x is not in the model. I guess now we can not use 1-step method since x is not in the model, but can only use 3-step method by setting x as AUXILIARY. Am I right? |
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Right. |
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