Use of goodness of fit statistics in Poisson GLMI'm using JMP Pro 15 to run a generalized linear model with a Poisson distribution and log link function. I was told to use Poisson because I have count data with values ranging from a min of 1 to a max of 118 with most falling in the 5 to 50 range. The model shows 2 goodness of fit statistics (pearson, deviance) that both have p-values less than 0.05. Does this mean that the model results are invalid and I need to reanalyze using a different distribution? This blog below seems to indicate that the results of the deviance test alone are somewhat unreliable.
https://thestatsgeek.com/2014/04/26/deviance-goodness-of-fit-test-for-poisson-regression/
AnalyticsRe: Use of goodness of fit statistics in Poisson GLMThe whole model LRT is significant. The goodness of fit tests indicate lack of fit. Perhaps include an interaction term?
What do the diagnostic plots look like?
Re: Use of goodness of fit statistics in Poisson GLMThanks Mark. There were some over-dispersion issues, I believe, with the data. This morning I tried a negative binomial distribution and that fit seems much better.
Re: Use of goodness of fit statistics in Poisson GLMDid you invoke the over-dispersion option in the launch dialog when you fit the Poisson distribution?
