Pseudo R^2 for logit - really naive question

I am using GLM to calculate logit models based on cross-sectional data.  I
am now down to the hard work of making the results intelligible to very
average readers.  Is there any way to calculate a psuedo analoque to the R^2
in standard linear regression for use as a purely descriptive statistic of
goodness of fit? Most of the readers of my report will be vaguely familiar
and more comfortable with R^2 than with any other regression diagnostics.

In fact, there are several "R^2-like" measures for logit and probit
models (not surprisingly, called "pseudo-R^2").  An overview is in:

"Pseudo-R Measures for Some Common Limited Dependent Variable Models"
http://citeseer.nj.nec.com/veall96pseudor.html

The Aldrich-Nelson measure appears to be the most widely used.

You may also want to consider Herron's (1999) "Expected Percent
Correctly Predicted" and related measures, described in Political
Analysis 8(1): http://web.polmeth.ufl.edu/pa/herron.pdf; even
traditional PCP/PRE measures tend to be quite informative (perhaps
even more useful than Pseudo-R^2).


Chris

Chris Lawrence <cnlawren at olemiss.edu> - http://www.lordsutch.com/chris/

Instructor and Ph.D. Candidate, Political Science, Univ. of Mississippi
208 Deupree Hall - 662-915-5765
-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
Send "info", "help", or "[un]subscribe"
(in the "body", not the subject !)  To: r-help-request at stat.math.ethz.ch
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._