How can I fix this error? form = @formula(y ~ (1 | a * b * c)) n = 1000 df = DataFrame( y=rand(Bool, n), a=CategoricalArray(rand('a':'z', n)), b=CategoricalArray(rand('a':'z', n)), c=CategoricalArray(rand('a':'z', n)), ) @time fit(GeneralizedLinearMixedModel, form, df, MixedMode…

The problem is you have a grouping variable a * b * c that isn’t supported. This isn’t supported because I haven’t seen a case where it makes sense statistically. Can you give us more context on the underlying statistical or scientific question you’re trying to address with such a model?

I have a bunch of observations from different groups in different locations and years. Each observation is (id, group, location, year, value). I wanted to estimate the average value in each (group, location, year). The sample size in each (group, location, year) varies, with some being small. I wa…

So you want a random intercept for each combination of group, location and year? Then you need a & b & c not a * b * c. The problem with (1|a * b * c) is that it expands to (1|a) + (1|b) + (1|c) + (1|a&b) + (1|a&c) + (1|b&c) + (1|a&b&c) which in most cases won’t be identifiable. That hopefully addr…

@jar1 does (1 | a & b & c) give you what you want? That’s what we use for things like the nesting syntax (e.g., (1 | a / b) lowers to (1 | a) + (1 | a & b) IIRC…that might be backwards)

Yes, I think that’s working for me. Thank you both.

GeneralizedLinearMixedModel no method matching _ranef_refs

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GeneralizedLinearMixedModel no method matching _ranef_refs

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