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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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