Belle <ping.yi <at> gmail.com> writes:
>
> Hi All,
>
> The data set that I have is a cluster data, and I want to run a HLM mixed
> model with multi-level response. Here is my data set:
> response:
[snip]
> library(MCMCglmm)
> y <- MCMCglmm(factor(Level) ~ Type+factor(yr>=2006)+Male+Ethnicity+ELL+
> avgTransfers+sdTransfers+agec+Disability+ELL*pctELL+Disability*pctDisability+
> pctMale+factor(yr>=2008)*factor(Grade),
> random=~Schoolid+Teacherid+Studentid,
> family="categorical", data=data[data$Grade>=4,])
>
> Error in MCMCglmm(FCATprofLevel ~ transferTypeCat + factor(yr >= 2008) + :
> please use idh(trait):units, us(trait):units or trait:units for error
> structures involving catgeorical data with more than 2 categories
>
> Does anyone know how I can fix it?
>
I would suggest (1) reading chapter 5 of the course notes vignette
carefully, if you haven't already [library("MCMCglmm");
vignette("CourseNotes")]. Especially see section 5.2 (which
begins "Multinomial models are difficult - both to fit and interpret.
This is particularly true when each unit of observation only has a
single realisation from the multinomial.")
(2) posting this to the r-sig-mixed-models mailing list
(say that you tried here first so no-one accuses you of cross-posting).
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