[R] Graphical presentation of logistic regression

Frank E Harrell Jr f.harrell at vanderbilt.edu
Wed Sep 14 13:29:11 CEST 2005

Beale, Colin wrote:
> Hi,
> I wonder if anyone has written any code to implement the suggestions of
> Smart et al (2004) in the Bulletin of the Ecological Society of America
> for a new way of graphically presenting the results of logistic
> regression (see
> www.esapubs.org/bulletin/backissues/085-3/bulletinjuly2004_2column.htm#t
> ools1 for the full text)? I couldn't find anything relating to this sort
> of graphical representation of logistic models in the archives, but
> maybe someone has solved it already? In short, Smart et al suggest that
> a logistic regression be presented as a combination of the two
> histograms for successes and failures (with one presented upside down at
> the top of the figure, the other the right way up at the bottom)
> overlaid by the probability function (ie logistic curve). It's somewhat
> hard to describe, but is nicely illustrated in the full text version
> above. I think it is a sensible way of presenting these results and am
> keen to do so - at the moment I can only do this by generating the two
> histograms and the logistic curve separately (using hist() and lines()),
> then copying and pasting the graphs out of R and inverting one in a
> graphics package, before overlying the others. I'm sure this could be
> done within R and would be a handy plotting function to develop. Has
> anyone done so, or can anyone give me any pointers to doing this? I
> really nead to know how to invert a histogram and how to overlay this
> with another histogram "the right way up".
> Any thoughts would be welcome.
> Thanks in advance,
> Colin

 From what you describe, that is a poor way to represent the model 
except for judging discrimination ability (if the model is calibrated 
well).  Effect plots, odds ratio charts, and nomograms are better.  See 
the Design package for details.

Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

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