Code I have used thus far without being able to replicate the
data includes:
Fm-lmer(Score~(1|Line%in%Set)+Set+(1|Block))
(I figured out how to get a p-value, but it didn't yield the
same results as those obtained in SAS)
%in% doesn't generally mean 'nested in' in R. It is a set
%in% doesn't generally mean 'nested in' in R. It is a set membership test
In a formula (involving a tilde) given to lm() or glm() %in% generally does
mean nesting.
attr(terms(y ~ (x1+x2) %in% (x3+x4+x5)), term.labels)
[1] x1:x3:x4:x5 x2:x3:x4:x5
but the | operator stops terms() from
I am trying to recreate a model that would mimic results a peer obtained
using SAS, but in R. The goal of this model would be to determine if there
is any variation among parental sets and lines (essentially is there a
significant p-value for the variables “set” and “line”). The problems I am
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