I'm following up on this great answer. Given the structure of my data (below), is it possible to add a random-effect for H
(a cluster ID variable) and X
(a categorical variable not varying in H
) as represented by the lme4
formula: ~ (1|H) + (1|X)
?
If yes, would that indicate that H
and X
are crossed random-effects even though NO value of X
is capable of meeting every value of H
as suggested by this answer?
Finally, under nested random-effects, we say correlations exist among observations coming from the same cluster, but how do correlations come about under crossed random-effects as in my case?
H X
1 2
1 2
2 1
2 1
2 1
3 2
4 1