Hi,

I have a dataset with 34 sites surveyed 3-5 times for two weeks. I have run a number of single season models with covariates. I am trying to narrow down the entire dataset to a set of candidate models. I haven't quite decided on the criteria for choosing the models to include in the candidate set but it will be something like models with a delta AIC value <2 or all the models whose weights sum to 0.95.

My question is what to do with models that could be included in the candidate set but have standard errors that are either excessively large or listed as -1.#IND00? In one case I have a model that clearly is the best model and the standard errors look fine but the untransformed value for psi leads me to a derived occupancy estimate that is almost zero despite the naive estimate of 0.33. Should I delete models from the dataset that have those types of issues or is there some other way I should treat them? Thank you!