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HB: optimal priors with categorical covariates

Hi! I'd like practical advice on the "rules-of-thumb" from the Model Explorer manual.

The rules of thumb specified there contain no comment about estimation with covariates. In my models, I use categorical covariates quite often, one covariate most of the time.

So I wonder, when considering the number of degrees of freedom, should one base it on the total sample size, or on the average number of respondents belonging to a category of the covariate?
For example, with a total sample of N=1200 and 4 nearly equally sized categories of the covariate, is it better to go for
d.f.=50 (N=1200) or
d.f.=5 (N=300)?

P.S. I have many parameters in the model, so it would take a tremendous amount of time for Model Explorer to do the search.

asked Oct 24, 2018 by IGaaa (250 points)
edited Oct 24, 2018 by IGaaa

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