```Date: Mon, 16 Jun 2003 10:43:18 -0400 Reply-To: "Handel, Richard W." Sender: "SPSSX(r) Discussion" From: "Handel, Richard W." Subject: Re: Nagelkerke R Square Content-Type: text/plain; charset="iso-8859-1" -----Original Message----- From: Christina Cutshaw [mailto:ccutsha1@JHEM.JHMI.EDU] Sent: Thursday, June 12, 2003 11:08 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 I recommend two introductory texts that are both outstanding: Applied Logistic Regression Analysis, Second Edition, Scott Menard Logistic Regression, A Primer, Fred Pampel Both are from the SAGE series and are inexpensive. My understanding is that there is no index in logistic regression that is "the same as" variance accounted for in OLS regression. For pseudo-R^2, Menard recommends the use of McFadden's R^2 instead of Naglekerke's, but you have to calculate it from the SPSS output. Good luck! Rick ****************************** Richard W. Handel, Ph.D. Assistant Professor Eastern Virginia Medical School Department of Psychiatry and Behavioral Sciences P.O. Box 1980 Norfolk, VA 23501 Phone: (757)-446-5888 Fax: (757)-446-5918 ```

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