Hello,

I am evaluating site covariates on probability of detection and probability of occupancy of triatomines in single season. Before constructing the models, I wanted to evaluate the existence of confusion by covariates, making a general model (of psi and p) with all the covariates and then removing each one, observing the presence or not of a change in the beta coefficients of the remaining covariates, considering as significant a change of 10%. I understand how this operates within the models of each parameter, as any logistic regression, but not for the other. Why would there be an effect of the covariate present in the model of detection on the coefficients of the covariates of the occupation model, for

example. I do not understand it and I'm not sure how to set the models to later see their adjustment through AIC, since the beta coefficients of covariates for one model change a lot depending on the variables that I include in the model of the other parameter . I am occupying the same covariates for the occupancy and detection models.

Finally, is it possible to evaluate interaction between independent variables with PRESENCE?

Regards