[R-sig-ME] FW: CLMM: Calculate ICC & Assessing Model Fit

David Duffy D@v|d@Du||y @end|ng |rom q|mrbergho|er@edu@@u
Sun Aug 23 09:14:46 CEST 2020


> The distribution across the 9 levels appears rather haphazard, which dissuaded me from trying a GLMM:

Maybe. A certain amount of that can be soaked up by different intervals between thresholds in the probit-normal - floor and ceiling effects on your scale for the most extreme categories is one example. The equivalent of this for an ordinary LMM is an inverse-normal transformation of the scores (normit/rankit). This sometimes seems a bit lazy to me, but as I commented earlier, you may end up with similar results to the more elaborate models. Worth doing in parallel, at least.
Cheers, David Duffy.



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