I have a regression with a harmonic effect of day of the year, which interacts with other variables. I am not sure how to interpret the coefficients. My model is:
m1 <- lme(lcount ~ AirT + sin(2*pi/360*DOY) + cos(2*pi/360*DOY) + AirT*sin(2*pi/360*DOY) + AirT*cos(2*pi/360*DOY) + RainAmt + RainAmt*AirT, random = ~1|plot))
I get significant interaction effects of air temperature with the linearized harmonic day of the year (DOY) function. My response variable is the log of animal counts on each day. I want to describe how the effect of air temperature on animal observations changes depending on the day of the year.
Does anyone have suggestions on how I can interpret my beta values and/or how I can visualize the effect? I am using R but am not that skilled. The package I used for analyzing my data is nlme.
EDIT: My primary goals are (1) to describe the response of animals to environmental variables and (2) to predict future activity periods (i.e. when and under what conditions should a research bother trying to catch these animals). So if there is a better way to model this data, I would be interested in hearing it (such as cubic splines - see comments below).