I have a glmmTMB model and I used the overdisp and the zero_count functions with these results:
overdisp(glmmtmb_poisson) # Overdispersion test # # dispersion ratio = 0.2953 # Pearson's Chi-Squared = 3104.5094 # p-value = 1.0000 # # No overdispersion detected. zero_count(glmmtmb_poisson) # Observed zero-counts: 9946 # Predicted zero-counts: 9953 # Ratio: 1.00 # # Model is overfitting zero-counts
I am not sure what this means. I understand that the model is not overdispersed nor zero-inflated, but I am not sure what this overfitting means. Also, there was a notes saying that in the case of glmm a p value larger than 0.05 indicates overdispersion, yet the p value does not seem to indicate overdispersion in my case.
Should I just go ahead and run a simple glmmTMB model as my final model without any further worry about zero inflation and overdispersion?
Thank you very much!