I finally have packaged up a very rough port of my epcp routine from Stata to R as part of a package unimaginatively called cnlmisc; you can download it here. In addition to the diagnostics that the Stata routine provides, the glm method includes a bunch of R-square-like measures from various sources (including Greene and Long).

The only part I’m sure works at the moment is the epcp for glm objects (including survey’s and Zelig’s wrappers thereof); the others that are coded (for polr and VGAM) are probably half-working or totally broken, and some wrappers aren’t there yet at all. The error bounds suggested by Herron aren’t there either. The print routines need a lot of work too; eventually it will have a nice toLatex() wrapper as well. But it beats having it sit on my hard drive gathering dust; plus I may eventually get motivated to write a JSS piece or something based on it.

epcp for Stata is still available at my site. For more information on the measure, see Michael C. Herron (1999), “Postestimation Uncertainty in Limited Dependent Variable Models” Political Analysis 8(1): 83–98 or Moshe Ben-Akiva and Steven Lerman (1985), Discrete Choice Analysis, MIT Press.