[R] warnings associated with logistic regression

Prof Brian D Ripley ripley at stats.ox.ac.uk
Tue Jul 11 18:36:37 CEST 2000

On 11 Jul 2000, Allan Strand wrote:

> Hi all,
> This is as much as statistical/estimation question as an R-specific
> one, but here goes.
> I am trying to use logistic regression to predict suitability of
> habitats for certain plant species.  The response variable is a binary 
> one that indicates whether a particular species is found at a site on
> the landscape.  The independent variables represent physical
> characteristics of the landscape derived from a GIS.  A significant
> proportion of the time I get the following warning messages from
> glm():
> > lr <- glm(known.v1~elevation+aspect+slope+energy15+energy166+aspect+accum+streams.buffered,family=binomial,data=siteframe)
> Warning messages: 
> 1: Algorithm did not converge in: (if (is.empty.model(mt)) glm.fit.null else glm.fit)(x = X, y = Y,  
> 2: fitted probabilities numerically 0 or 1 occurred in: (if (is.empty.model(mt)) glm.fit.null else glm.fit)(x = X, y = Y,  
> Now I can get the algorithm to converge (or at least not produce the
> warning) by increasing the number of iterations, but that does not
> affect the second warning.  A read of Hosmer and Lemeshow (1989) does not
> provide much insight, so I thought that I would post the question  to
> the list.
> Any comments? Also, I'd be happy to email a dataset that exhibits this
> behavior if anyone is curious enough.

It usually means that your dataset exhibits complete separation, and so a
logistic regression can fit perfectly. All the diagnostics (p-values etc)
are then (very) unreliable. There are also concepts of partial separation,
where only some of the cases are fitted perfectly, but similar comments

This is shamefully missed in most statistics books, but is well known in
the AI community, which used to seek such fits (as `perceptrons') and
do again (as `support vector machines') Santer & Duffy is the only
contingency-tables book I know that covers this, as does my (1996) Pattern
Recognition and Neural Networks book.

Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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