Message/Author 

adel powell posted on Saturday, December 17, 2011  4:05 pm



Hi, I am trying to generate multilevel categorical data. I am trying to study various aspect of that type of data. I am having problems. My data is ordinal but nonnormal. I am getting this error: *** ERROR in MODEL command Variances for categorical outcomes are not allowed on the within level. Variance given for: Y1 Can Mplus not do multilevel modeling on categorical noncontinuous data? I was thinking Mplus can treat the data like Logistical multilevel modeling where the within error is estimated by pie/3. I forgot the exact figure? 


Yes, Mplus can do this. But with categorical outcomes there is not a free withinlevel variance parameter so you can't estimate/mention that in the MODEL command, which is what the error message complains about. As you say, with logit link the residual variance is pisquare/3, that is, a fixed quantity, not a free parameter. Mplus uses that fixed quantity implicitly. 

Cecily Na posted on Friday, March 01, 2013  8:29 am



Hi Linda and Bengt, I have a categorical outcome (three levels) in a twolevel model. The model syntax is as following, (A, B are predictors at the within level, C is the categorical outcome, and D is the predictor at the between level). Is the following syntax correct? Why is the model syntax for categorical outcomes the same as for continuous outcomes? %Within% C ON A B; %Between% C ON D; In a multilevel model for continuous outcome, the intercept or slope of the within level outcome is modeled as random and treated as a latent factor at the between level. For categorical outcome, what is modeled as random? Thanks a lot! 


The model you specify above is a random intercept model both for a continuous or categorical outcome. See Example 9.3 where one outcome is continuous and one outcome is categorical. 


the Output for my analysis has also returned: "Variances for categorical outcomes are not allowed on the within level." Is there a way to estimate a free parameter for item variances for the within level using ordinal data in version 7? I am trying to estimate the withinlevel reliability of a 12 item scale, and need residual variance estimates for each item to do so. 


Variances of categorical variables are not parameters in the model. See the following paper which would deal with this: Raykov, T., Dimitrov, D.M. & Asparouhov, T. (2009). Evaluation of scale reliability with binary measures using latent variable modeling. Forthcoming in Structural Equation Modeling. 

Yoosun Chu posted on Monday, October 02, 2017  5:37 pm



Hello, I am running twolevel sem. My dv items are continuous, but in the within level, I have some covariates (gender, education, etc), that are categorical. I treated them as exogenous variables. I have an error message: variances for categorical outcomes are not allowed on the within level. Can mplus handle this? I read the above conversation, but it is still not clear for me. Thanks. 


You should not refer to variances for categorical outcomes because they are not free parameters to be estimated. But the question is why you have categ vbles as DVs. Perhaps you are incorrectly referring to your IVs as categorical. If this doesn't help  send output to Support along with your license number. 

Xi Chen posted on Saturday, November 23, 2019  4:12 pm



Hi, Is it possible to get ICC for a categorical variable? Can I use betweenlevel variance/(betweenlevel variance + pisquared/3) to calculate ICC for a categorical variable? Thanks! 


That's correct for logit link. 

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