I've been trying to build a three-level analysis of student survey data on the relationships between teaching practices and cultural background (SES as covariate) on science achievement.
The response items in the dataset is inherently categorical and ordinal (Likert-scale items) in nature. After having run variables of each level to see how they will run independently, I just tried to combine the levels only to get the following error:
Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, : MxExpectationRAM: Ordinal indicators are not supported in multilevel models
It hadn't occurred to me that this could be a problem, and it puts me in somewhat of a predicament about how to proceed. Searching through some old forum threads, I did find a thread that discusses this topic [6], with a comment suggestion using mxFitFunctionAlgebra()
and mxEvaluateOnGrid()
[7]. However, I would not know how to proceed with that.
Has there any more developments on this issue? If there's no direct solution, I would need to consider workarounds or alternative strategies. The simplest alternative for the ordinal level 2 and 3 variables would be to model them as continuous. However, this does not seem like a good idea for variables which do not have any semblance of a normal distribution.
Any suggestions how to proceed, or any code examples or similar that addresses this issue, would be appreciated.