Independent observed variables ("x" variables in Mplus terminology) should not be declared nominal, but should instead be broken up into a set of dummy variables appearing on the RHS of ON. I assume that your independent nominal variable is not in turn predicted by another variable, in which case something different needs to be done.
freek bucx posted on Monday, March 19, 2007 - 4:18 am
Thanks for your answer. The latter is however the case: my independent (nominal) variable (with four categories) is also predicted itself by other variables. How can I fix this in Mplus?
The only way to do this is to create a categorical latent variable that is equal to the nominal observed variable and use the categorical latent variable in the regression. For example, if you have a model:
x -> u -> y
where u is a nominal variable, after you create a categorical latent variable c which is equal to u, you will have
x -> c -> y
where c is a categorical latent variable with four classes. The relationship between x and c is the multinomial regression of c on x and the relationship between c and y is found in the class-varying means of y.
Hi, I wanna to create a latent variable (L) which is measured by C (4 level categorical variable) and N (nominal variable as indicated by 0 & 1) to reflect the demo characteristics, where IV is independent variable, M is mediator and DV is dependent variable.
L by C N; IV on L; D on M IV; M on IV L;
nominal = N#1 N#2;
however, error message prompt for unknown nominal variable, how can I fix this problem?
And, If an indicator belongs to two latent factors, how to interpret this structure? How about if two indicators of two latent factors are correlated?