I just fit a model in lme4, and I'm wondering what the heck I fit...
I have individuals
id, and each is measured pass/fail on items that can be described using two factors,
f2. My theory says that
f2 can interact. So I want to compare these models:
# f2 doesn't matter m1 <- lmer(pass ~ f1 + (1|id), family="binomial") # f2 is a fixed effect, doesn't interact with individuals m2 <- lmer(pass ~ f1 + f2 + (1|id), family="binomial") # f2 is a nested random effect, interacting with individuals m3 <- lmer(pass ~ f1 + (1|f2/id), family="binomial")
First, am I right that there's a random effect of each level of f2, and each individual's level of f2 is partially pooled, depending on the number of observations for that individual?
Second, does it make sense to fit
f2 as a fixed effect with random individuals nested within each level of
f2? How does one write that?
Third, what's this, with f2 and id reversed in the formula? I typed it by accident, but now I want to understand it.
m3weird <- lmer(pass ~ f1 + (1|id/f2), family="binomial")