These are very simple questions which I think will be most easily answered
conceptually and without any data.

First, does MCMCglmm allow for specification of varying slopes vs. varying
intercepts?  In the call's most basic form,

m<-MCMCglmm(outcome~fixed_effect, random=~cluster, family="ordinal",
data=data, prior=prior),


is the outcome 'intercept' or the slope of 'fixed_effect' varying by
'cluster'?

Second, as I understand it the model cannot be fit with a nested data
structure (ie, varying at multiple levels e.g. modeling child test scores
within schools within districts).  However, can effects vary across two
clustering levels if they are not nested (e.g., modeling tests within
schools and by religion)?  If so, how is the model specified?

Thanks very much in advance.

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