Date:         Tue, 17 Jun 2003 09:42:23 -0700
Reply-To:     "Johnson, Will@DSS" <Will.Johnson@dss.ca.gov>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         "Johnson, Will@DSS" <Will.Johnson@dss.ca.gov>
Subject:      Re: Nagelkerke R Square
Comments: To: Christina Cutshaw <ccutsha1@JHEM.JHMI.EDU>
Content-Type: text/plain; charset="iso-8859-1"

Dear Christina,

I read Hosmer and Lemeshow's 1989 edition of "Applied Regression Analysis",
which is widely used.  SPSS includes the Hosmer-Lemeshow goodness of fit
test for logistic regression models.  In their 1989 book they pan measures
of variance explained in logistic regression as lconceptually inappropriate
for logistic regression.  I'm curious what others will say about this
subject.

Will Johnson

-----Original Message-----
From: Christina Cutshaw [mailto:ccutsha1@JHEM.JHMI.EDU]
Sent: Thursday, June 12, 2003 8:08 PM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: Nagelkerke R Square


List Members,

As part of my dissertation, I ran a binary logistic regression model
(N=73, Outcome present n=22, outcome absent n=53).  I have three
variables in the model: one nominal (a) one dichotomous (b)and one
continuous (c) .  The model contains the three main effects a, b,and c,
and one interaction term a*b.  The Nagelkerke R Square is 0.479.  I
understand that this is a "pseudo R-squared" measure because this is a
logistic versus linear regression, but could someone explain to me how
to understand what it is calculating and how to explain variance
accounted for in logistic regression?  I have never seen this measure
used in journal articles using logistic regression.

Thanks!

Chris Cutshaw