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Is there any ubiquitous (or not so much) graphical method in count response models (e.g. Poisson GLM) to diagnose conditional zero-inflation? I'm aware of statistical tests that can be used for that, but I'm specifically interested in a diagnostic visualization. Some things I've thought of:

  • Looking at marginal response distribution might give you a hint, but it's certainly not completely reliable in terms of describing zero-inflation conditioned on predictors.
  • The residuals-vs-fitted: I'm not quite sure what exactly to look at over there to diagnose this particular aspect of zero-inflation
  • The residuals-vs-true values: over here at least I know that I should be focusing on the 0-true values and what kind of errors were committed on them, but what kind of pattern should I expect there? Vast number of strongly negative residuals (due to consistent over-estimation of zeros)?
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