SUG 1.13 ("Multivariate priors for hierarchical models"): missing prior & serious identification issue?

Well, now this is embarassing. I just worked out a series of forgettings on my part that led to my wasting of folks’ time here. First, in the recent entries here I forgot that in the post that kicked off the thread I’d worked out that my code and that of SUG 1.13 were identical (as @jsocolar poipnts out), and it’s the data declaration that I thought implied a difference/identifiability issue. Furthermore, this latter was itself forgetting that SUG 1.13 uses data/terminology that’s different-but-deceptively-similar to my typical data/terminology.

Specifically, it speaks of individuals associated with individual-level predictors, and individuals are lumped together in groups that are in turn associated with group-level predictors. Importantly, there’s only one observation of each individual.

 I Ip1 Ip2 ...  G Gp1 Gp2 ...
i1   +   - ... g1   +   - ... 
i2   +   - ... g1   +   - ... // i1 & i2 share the same Ip's
i3   -   + ... g1   +   - ... 
i4   -   + ... g1   +   - ... // i1:i4 share the same Gp's; i3 & i4 share the same Ip's
i5   +   - ... g2   -   + ... 
i6   +   - ... g2   -   + ... // i5 & i6 share the same Ip's
i7   -   + ... g2   -   + ... 
i8   -   + ... g2   -   + ... // i5:i8 share the same Gp's; i7 & i8 share the same Ip's

Whereas the way I typically have data structured, I still speak of individuals and groups, but of within-individual predictors and between-group predictors. This works out to meaning what SUG 1.13 calls a group, I call an individual, and what SUG 1.13 calls an individual, I call a trial:

 t Ip1 Ip2 ...  I Gp1 Gp2 ...
t1   +   - ... i1   +   - ... 
t2   +   - ... i1   +   - ... // t1 & t2 share the same Ip's
t3   -   + ... i1   +   - ... 
t4   -   + ... i1   +   - ... // t1:t4 share the same Gp's; t3 & t4 share the same Ip's
t5   +   - ... i2   -   + ... 
t6   +   - ... i2   -   + ... // t5 & t6 share the same Ip's
t7   -   + ... i2   -   + ... 
t8   -   + ... i2   -   + ... // t5:t8 share the same Gp's; t7 & t8 share the same Ip's

Using my terminology, if there were only one observation per combination of individual and within-individual predictors, then there would be identifiability issues as I was concerned about at the outset of this thread and the alternative multivariate I posted would be more appropriate. But I see now that this isn’t an issue for the data as discussed in SUG 1.13 and I was just forgetting the terminology-mapping 🤦

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