Hi,
I'm curious if anyone has dealt with a c-hat of 0.000 when running a GOF test in PRESENCE. When I ran the GOF test on my most parameterized model I saw that it had a c-hat value of 1.8 (indicating overdispersion in which I should adjust and use the QAIC to rank models). However, after running more simplified models and settling on a top model, I was surprised to see that the c-hat value was 0.000. I assumed that once I simplified the models I would still have an overdispersed model that I would have to adjust, so I'm not sure how to interpret or handle the 0.000 score.
I did some reading in the forums and the MARK book, and it seems like the verdict for what to do with c-hat < 1 is still undecided in the literature. I know this typically implies underdispersion, but I'm not sure if there is something I may have been overlooking when I ran my models. Some forum posts suggested that this could be a result of sparse data, which I certainly have, but I do not know if there is something I can do to counter this problem. A score of 0.000 seems incredibly low and I'm not sure what it could mean.
Any insight into this problem would be greatly appreciated!
~Holly