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
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
-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, typically y is a factor with two levels (indicating
success/failure) instead of a numeric vector on [0, 1]. Perhaps the
description in the book is not so clear. You should interpret data on
proportions as the observations from a Binomial distribution (rather
than we observed
Dear David,
David Winsemius wrote:
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?
I am not questioning the approach. I am only trying to understand why a
(rather expensive) source of
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
On Mar 30, 2010, at 11:19 AM, Corrado wrote:
Dear David,
David Winsemius wrote:
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?
I am not questioning the approach. I am only trying to
G'day all,
On Tue, 30 Mar 2010 16:19:46 +0100
Corrado ct...@york.ac.uk wrote:
David Winsemius wrote:
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?
I am not questioning the
Corrado
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
At 12:08 PM 3/30/2010, David Winsemius wrote:
snip
I don't understand this perspective. You bought Crowley's book so he
is in some minor sense in debt to you. Why should you think it is
more appropriate to send your message out to thousands of readers of
r- help around the world (some of whom
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