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According to Frank Harrell's useR2010 keynote on Information Allergy: Never. Edit: And here is a long list of reasons why one should not categorize continuous variables (which is the same thing, but expressed in more statistical terms). And for completeness, here is Andrew Gelman debating the issue some more.


The issues pointed out in the various footnotes and references here do not seem to address this issue. There are numerous situations where detailed intelligent binning is not only appropriate, but adds value to the model. Let's break it down to the basics, which is that in a digital world every thing is categorical. We never measure AGE down to the second, ...


Have you looked at the bivariate probit model at all? Bivariate probit model with sample selection assumes that the distribution of the accepted applicant population is different from that of the rejected applicant population. That is, it is assumed that $P(default|X, rejected) \neq P(default|X, accepted)$ for some vector of ...

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