Hi,

I am fitting a generalised linear model on binomial data. Although I know overdispersion is much more common, I am pretty sure that my data are actually underdispersed. My two clues for this are that, in 99.8% of replications, the generated data had greater variance than the dataset; and also, plots of the residuals by the number of successes show a decreasing linear trend, indicating that for a low number of predicted successes, the number of successes is actually higher, and vice versa.

For overdispersed data, I have previously used the beta binomial, but I am unsure what to do with this underdispersed data. Does anyone have any advice for how to do this in Stan?

Please let me know if you need any additional information!

Thanks,

Martin