# Relative Variable Importance with Model Averaging

I am doing occupancy analysis for mammals using data derived from camera traps. I've fit the model using Rmark, dredged for the p covariates by fixing psi covariates, then performed model averaging to determine which p covariates I should keep. the results for the full averaged model gives me this relative variable importance:

Relative variable importance:
Psi(Phase) p(WeekDay) p(Trail) Psi(Zone) p(DetectionDist) Psi(Phase:Zone)
Importance:          0.53       0.47       0.38     0.34      0.28             0.01
N containing models:   24         20         19       24        20                8


Is there a rule of thumb about what the importance should be for those covariates which I should discard? To me, it looks like all the p covariates should be retained but the Psi covariate of (Phase:Zone) should be discarded, although I dont know if I can make this assumption since this was dredged fixing the psi covariates. Thoughts?