Dear Ruben
I am afraid not .... the paragraph's title is a bit of a give away:
Proportion Data and Binomial Errors
The sentence reads:
" .... are dealt with by using a generalised linear model with a
binomial error structure".
with the example:
glm(y~x,family=binomial)
You can check at page 514/515.
Rubén Roa wrote:
-----Mensaje original-----
De: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] En
nombre de Corrado
Enviado el: martes, 30 de marzo de 2010 16:52
Para: r-help@r-project.org
Asunto: [R] From THE R BOOK -> Warning: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
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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