[R] correlation predictors problem

[Prof Brian Ripley]

On Tue, 11 Sep 2001, Robert Espesser -- CNRS wrote:

> R colleagues,
>
> I want
> to get the correlation between the coefficients of a regression.
> Everything seems OK, but when there are more than 3 regressors, the
> correlation matrix is completely wrong, as follows:
>
> > x.glm <- glm( bascule  ~durP+  durI +durC+moyHzPB +moyHzIN, x,family=binomial)
> > summary(x.glm,correlation=T)
>
> Call:
> glm(formula = bascule ~ durP + durI + durC + moyHzPB + moyHzIN,
>     family = binomial, data = x)
>  .......
> ........
> (Dispersion parameter for binomial family taken to be 1)
>
>     Null deviance: 365.00  on 266  degrees of freedom
> Residual deviance: 305.72  on 261  degrees of freedom
> AIC: 317.72
>
> Number of Fisher Scoring iterations: 3
>
> Correlation of Coefficients:
>         ( dP dI dC mHP
> durP      1
> durI         1
> durC            1
> moyHzPB .          1
> moyHzIN ,
> attr(,"legend")
> [1] 0 ` ' 0.3 `.' 0.6 `,' 0.8 `+' 0.9 `*' 0.95 `B' 1

Notice the legend.  You don't have the correlation matrix but a
representation of it.

This is one of those things that certain people are keen on, and so
make the default for others.

You want

print(summary(x.glm,correlation=TRUE), symbolic.cor = FALSE)

I do think there should be a global option to turn this on, it being off
by default.  It's not even a documented argument in current R (but will be
in 1.4.0).

-- 
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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