[R] Weights in binomial glm

[Jan van der Laan]

Thierry,

Thank you for your answer.

>From the documentation it looks like it is valid to assume that the
weights can be used for replicate weights. Continuing your example:

dataset$Success2 <- dataset$Success
Aggregated2 <- cast(Person+Success ~ ., data = dataset, value =
"Success2", fun =list(mean, length))
m2 <- glm(mean ~ 1, data = Aggregated2, family = binomial, weights =length)

In this case the weights can be seen as replicate weights. In my case
the proportion of successes for each group is either 0 or 1.

I am familiar with the survey package. However, in this case there
should not be difference between the two as far as the parameter
estimates are concerned (the standard errors are incorrect for glm).

The strange thing in this case is that the estimates seem to depend on
the scaling of the weights, which should not be the case. Also in your
example scaling the weights gives the same estimate:

m1 <- glm(mean ~ 1, data = Aggregated, family = binomial, weights = length/10)

Regards,
Jan



On Fri, Apr 16, 2010 at 3:19 PM, ONKELINX, Thierry
<Thierry.ONKELINX at inbo.be> wrote:
> Jan,
>
> 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.
>
> library(boot)
> library(reshape)
> 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 =
> length)
>
> inv.logit(coef(m0))
> inv.logit(coef(m1))
>
> Have a look at the survey package is you want to analyse stratified
> data.
>
> Thierry
>
> ------------------------------------------------------------------------
> ----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek
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>
> Research Institute for Nature and Forest
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>
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> Thierry.Onkelinx at inbo.be
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>
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>
>> -----Oorspronkelijk bericht-----
>> Van: r-help-bounces at r-project.org
>> [mailto:r-help-bounces at r-project.org] Namens Jan van der Laan
>> Verzonden: vrijdag 16 april 2010 14:11
>> Aan: r-help at 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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