I am attempting a single-season occupancy model with 3 survey periods. In the third survey, there were no detections (I have a column of only 0s). The first two columns have a combination of 1s and 0s.
I found a previous post (http://www.phidot.org/forum/viewtopic.php?f=11&t=2299&p=7125&hilit=no+detections+in+survey#p7125) about this issue, but need a bit of clarification on this quote:
jhines wrote:If you have covariates, you won't be able to model the surveys with no detections as a function of the covariates as there is no variation in detection to model. If there is very little variation in the covariates, or sparse data, models with covariates might not converge.
I would like to model survey-specific covariate effects on p for this single-season model, and obviously this will also be an issue when I attempt multiseason models using this data set, although all other survey periods for other years have detections.
So in order to do models of the form psi(.),p(covariate), with what value should I fix the parameter p[3]? And will the design matrix be as follows?
psi: a1=1
p1: b1=1, b2=covariate
p2: b1=1, b2=covariate
p3: b1=0, b2=0
Thank you for your time!
Daisy