A) It is not an error, only a warning. Wouldn't it seem reasonable to
issue such a warning if you have data that violates the distributional
assumptions?
B) You did not include any of the data
C) Wouldn't this be more appropriate to the author of the book if this
is "exactly what was suggested" there?
--
David,
On Mar 30, 2010, at 10:51 AM, Corrado wrote:
Dear friends,
I am testing glm as at page 514/515 of THE R BOOK by M.Crawley, that
is on proportion data.
I use glm(y~x1+,family=binomial)
y is a proportion in (0,1), and x is a real number.
I get the error:
In eval(expr, envir, enclos) : non-integer #successes in a binomial
glm!
But that is exactly what was suggested in the book, where there is
no mention of a similar warning. Where am I going wrong?
Here is the output:
> glm(response.prepared~x,data=dddd,family=binomial)
Call: glm(formula = response.prepared ~ x, family = binomial, data
= dddd)
Coefficients:
(Intercept) x -0.3603 0.4480
Degrees of Freedom: 510554 Total (i.e. Null); 510553 Residual
Null Deviance: 24420
Residual Deviance: 23240 AIC: 700700
Warning message:
In eval(expr, envir, enclos) : non-integer #successes in a binomial
glm!
>
Regards
--
Corrado Topi
PhD Researcher
Global Climate Change and Biodiversity
Area 18,Department of Biology
University of York, York, YO10 5YW, UK
Phone: + 44 (0) 1904 328645, E-mail: ct...@york.ac.uk
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David Winsemius, MD
West Hartford, CT
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