R help - Mar 2010 - 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: ct529 at york.ac.uk

-----Mensaje original-----
De: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] En
nombre de Corrado
Enviado el: martes, 30 de marzo de 2010 16:52
Para: r-help at 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: ct529 at york.ac.uk

---

Probably you are misreading Crawley's Book?
A proportion would usually be modeled with the Beta distribution, not the
binomial, which is for counts.
If you are modeling a proportion try the betareg function in betareg package.
HTH
Ruben
 


____________________________________________________________________________________

Dr. Rub?n Roa-Ureta
AZTI - Tecnalia / Marine Research Unit
Txatxarramendi Ugartea z/g
48395 Sukarrieta (Bizkaia)
SPAIN

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: ct529 at york.ac.uk
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
West Hartford, CT

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 some proportion data which fell in [0,1]). E.g.

y=rbinom(10, size = 1, prob = .3); x=rnorm(y)
# or y = factor(y)
glm(y~x, family = binomial)


Regards,
Yihui
--
Yihui Xie <xieyihui at gmail.com>
Phone: 515-294-6609 Web: http://yihui.name
Department of Statistics, Iowa State University
3211 Snedecor Hall, Ames, IA



On Tue, Mar 30, 2010 at 9:51 AM, Corrado <ct529 at york.ac.uk>
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: ct529 at york.ac.uk
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>