[R] Weights in binomial glm

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Fri Apr 16 15:19:55 CEST 2010


It looks like you did not understand the line "For a binomial GLM prior
weights are used to give the number of trials when the response is the
proportion of successes."

Weights must be a number of trials (hence integer). Not a proportion of
a population. Here is an example that clarifies the use of weights.

dataset <- data.frame(Person = c(rep("A", 20), rep("B", 10)), Success =
c(rbinom(20, 1, 0.25), rbinom(10, 1, 0.75)))
Aggregated <- cast(Person ~ ., data = dataset, value = "Success", fun =
list(mean, length))

m0 <- glm(Success ~ 1, data = dataset, family = binomial)
m1 <- glm(mean ~ 1, data = Aggregated, family = binomial, weights =


Have a look at the survey package is you want to analyse stratified


ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Gaverstraat 4
9500 Geraardsbergen

Research Institute for Nature and Forest
team Biometrics & Quality Assurance
Gaverstraat 4
9500 Geraardsbergen

tel. + 32 54/436 185
Thierry.Onkelinx op inbo.be

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> -----Oorspronkelijk bericht-----
> Van: r-help-bounces op r-project.org 
> [mailto:r-help-bounces op r-project.org] Namens Jan van der Laan
> Verzonden: vrijdag 16 april 2010 14:11
> Aan: r-help op r-project.org
> Onderwerp: [R] Weights in binomial glm
> I have some questions about the use of weights in binomial 
> glm as I am not getting the results I would expect. In my 
> case the weights I have can be seen as 'replicate weights'; 
> one respondent i in my dataset corresponds to w[i] persons in 
> the population. From the documentation of the glm method, I 
> understand that the weights can indeed be used for this: "For 
> a binomial GLM prior weights are used to give the number of 
> trials when the response is the proportion of successes."
> >From "Modern applied statistics with S-Plus 3rd ed." I understand the
> same.

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