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Does anyone have an example of code including nominal, categorical, and continuous variables in a CFA. I know MPLUS can do this, but cant find an example of it. Thanks, Josh 


Don't know that I have an example handy, but you mix a little bit of UG ex 3.15 with a little bit of UG ex5.14. Maximumlikelihood estimation with numerical integration has to be used. 


You can try out the data and input for UG ex5.2 and change CATEGORICAL to NOMINAL and see what happens. 


If you make that switch in example 5.2 you get the following error message Nominal variables must be specified with a threshold number: U1 and so on for the other variables. 


Ok, so say f BY u1#1 u1#2 (assuming 3 nominal categories) etc 


Hi, I hope you are well. I am trying to fit a NRM model with items having 4 options using the "Nominal Are" option in Mplus. I am modeling the 3 response option with the reference one being the correct response (I have recoded the data). I am modeling the first response options' slope with a (*) and all intercepts in brackets. I have a couple of questions: 1. Am I correct in assuming that the slopes and intercepts I am getting in the output are specific of the three distractors? Do I interpret the intercepts as e.g. differences in ability between individuals who select this distractor compared to the correct response or are these intercepts mean ability levels of individuals selecting that distractor? 2. If I use a two factor model with the second factor being another group, for potentially testing differences between groups, do I need to constrain the correlation between the two factors to zero? 3. If the two factors define two different populations do I need to set for both populations the variances to one and the means to zero? thank you in advance for your help. George 


1. The parameterization and its interpretation is that of a regular multinomial logistic regression model. This is also described in chapter 4 of the new Handbook of IRT, Vol 1, edited by van der Linden. It refers back to Bock's 1972 article in Psychometrika. 2. I don't know what you mean by "the second factor being another group". Perhaps you mean a second set of items. The factor correlation does not have to be zero. 3. I don't know how two factors can define two different populations if by population you mean a set of subjects. But perhaps you refer to a population of items (an item bank). 

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