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2 of the variables in my SEM are categorical observed, whereas the other 4 are latent (with indicators, of course). When specifying my SEM in M+, should I treat the observed variables (i.e., F5 & F6) in the same way as my latent (i.e., F1-F4): E.g., F4 ON F3; (both continuous latent vars) F3 (latent var) ON F5 (categorical var); |
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Actually, I am just confused about using categorical/binary variables in my SEM. Basically, I have 2: sexual orientation and participation in sports. Both are yes/no variables. For example, either one participates in sports yes (1) or no (2). I am simply confused about how to represent these in the model in M+. If you could point me in a direction, I would appreciate it. |
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Given that all of my other variables are continuous. |
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The scale of an independent variable is not an issue is regression. Your only categorical variable is an independent variable. You don't need to do anything. |
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Thank you |
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Luo Wenshu posted on Saturday, December 23, 2017 - 5:39 am
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Dr. Muthen, if I have both observed variables and latent variables as predictors for some latent outcome variables, do I need to specify correlations between the observed and latent predictors? It seems by default they are not set to be correlated in Mplus. Thank you! |
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Yes. |
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