Hi folks,
This has likely been asked before, so please feel free to link any relevant posts . . .
I am looking at a network of 300+ households. The outcome variable is dichotomous -- i.e., does Household A share food with Household B? Because food can flow both ways, one row in the dataset is for Household A to Household B, and then there's another row for B to A. So I'd like to add a random effect for the dyad (DyadID). In addition, some households just generally give more, and others generally receive more, so I'd like to add random effects for donating households (GNO) and receiving households (RNO).
My impression was that it's possible to fit cross-classified random effects using numerical integration in lme4. However, when I try to fit an empty model using this code:
model.empty <- glmer (Sharing ~ 1 + (1|DyadID) + (1|GNO) + (1|RNO),family = binomial, nAGQ=10)
Then I get the following error message:
Error in validObject(.Object) :
invalid class "mer" object: AGQ method requires a single grouping factor
Any advice on what I can do?
Many thanks,
Jeremy
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