[R] Logistic regression: At times correlation matrix of coefficients gets messed up

[Prof Brian D Ripley]

It's not messed up, just someone's idea of a compact display.

Options are

1) Use vcov(fit) instead

2) Use print(summary(fit), symbolic.cor=FALSE)

Does anyone think that the current arrangement (use this scheme for more
than 4 coefficients) is sensible?  Surely the abbreviations are not
("(" for intercept?), and why is the diagonal being shown but the top row
and last column have been omitted?   If the whole matrix was shown, the
column labels could be omitted.

I'd much prefer symbolic.cor=FALSE to be the default.

On Mon, 20 Jan 2003, Pankaj Choudhary wrote:

>
> Hi,
>
> When I include a categorical variable (RACE with 3 levels - "white",
> "black" and "other") in my logistic regression model, the correlation
> matrix of the coefficients gets messed up. I get something like:
>
> -----------------------------------------
> Correlation of Coefficients:
>           ( A L RACEb
> AGE       , 1
> LWT       ,   1
> RACEblack       1
> RACEother .     .
> attr(,"legend")
> [1] 0 ` ' 0.3 `.' 0.6 `,' 0.8 `+' 0.9 `*' 0.95 `B' 1
> -------------------------------------
>
> I couldn't figure out how to interpret it. Here is the sequence of
> commands and the complete output. (I am using R 1.6.2)

-- 
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 272866 (PA)
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