I have a residual vs fitted values plot for the following negative binomial model:
glm.nb(formula = Numberpertow ~ as.factor(CruiseID) + as.factor(Stratum) + offset(log((TowDist * Subsampling_fraction)/1850)), data = news2,link = log)
Numberpertow is discrete count data Cruise and Stratum are catergorical covariates. Cruise has 3 levels and stratum has 23 levels.
The plot below is of the deviance resiuals against the log of the fitted values. I am trying to assess model fit. Based on this plot the residuals dont appear to be centered around zero for larger fitted values and I can see a pattern of decreasing residuals for larger fitted values. I am wondering if there is enough deviation from expectations to not continue with this model. The scale location plot does not indicate heteroskedasticity.