I have modeled whether a bird is detected by an antenna (1=yes, 0=no) with the following predictor variables: length of visit, species, and site. Individual ID is a random effect.
I am not also wondering, and think it could be valuable to see whether a bird took a seed(1=yes, 0=no) would also determine whether a bird is detected by an antenna.
So the model would look like this:
mod <- glmer(success_rfid ~ length + species + site + success_seed + (1|id), family = binomial( link = "logit"), data = data)
The output looks like this:
summary(mod) Fixed effects: Estimate Std. Error z value Pr(>|z|) (Intercept) -4.4283 0.9780 -4.528 5.95e-06 *** length 0.1921 0.1205 1.594 0.1110 speciesTUTI 1.5201 0.7887 1.927 0.0539 . speciesWBNU 1.2716 0.8844 1.438 0.1505 siteL3 -0.7220 0.7591 -0.951 0.3415 siteYB2 -0.1024 0.8637 -0.119 0.9057 success_seed1 3.1105 0.7296 4.263 2.01e-05 ***
My initial reaction is "Oh, no I can't do this. Length of a visit predicts success of taking a seed. Those are correlated and couldn't be in the model."
And then I'm left wondering what to do.