Measuring overlap in binary regression

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On Robustness Properties of Convex Risk Minimization Methods for Pattern Recognition (2004, unknown): “For a numerical comparison between the support vector machine and the regression depth method recently proposed by Rousseeuw and Hubert (1999) see Christmann and Rousseeuw (2001) and Christmann et al. (2002).”
The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression (2018, background): “Finally, [4] analyzes the notion of regression depth for measuring overlap in data sets.”
The Constraining Power of International Treaties: Theory and Methods (2005, background): “…the non-quasi-complete separation assumption of logit and probit models: for probit models to render consistent estimates, they cannot include any independent variables that are perfect or quasi-perfect predictors of the dependent variable (Albert and Anderson 1984; Christmann and Rousseeuw 2001).”
On Maximum Depth and Related Classifiers (2005, methodology): “Christmann & Rousseeuw (2001) and Christmann et al. (2002) used the idea of regression depth (see e.g. Rousseeuw &Hubert, 1999) for classification between two competing populations.”