```Date: Tue, 17 Jun 2003 09:42:23 -0700 Reply-To: "Johnson, Will@DSS" Sender: "SPSSX(r) Discussion" From: "Johnson, Will@DSS" Subject: Re: Nagelkerke R Square Comments: To: Christina Cutshaw 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 ```

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