I'll cut to the chase. Here's what I'm doing:
- looking at the influence of water temperature and salinity on the presence of water-borne parasites for a certain estuarine bird population
- birds are checked for parasites 3 times a year for 5 years (Spring, Summer, Fall)
- this is mark-recapture, and some birds are sampled multiple times across years and seasons
- logistic regression is for water temp and salinity predicting parasites
Since some birds are included multiple times in my dataset (some twice a year, and many in multiple years), would it be wise to correct for multiple comparisons (Boneffori?) or am I thinking about this the wrong way?