Fulton wrote:
I’m running some logistic regressions and I’ve been trying to include weights
in the equation. However, when I run the model, I get this warning message:
Here’s what it says: Warning message: In eval(expr, envir, enclos) :
non-integer #successes in a binomial glm!
I think it is because the weights are non-integer values.
What is a good way to run logistic regressions in R when using non-integer
weights?
I’ve attached the output from the R console of the two different methods
I've tried.
The first regression is unweighted. The second regression includes the
weights in glm. The third regression includes the weights in svyglm.
However, despite using the same weights, I get contradicting results.
Perhaps I am misunderstanding how to use one or both of these functions.
You might be misunderstanding the use of weights in a binomial glm.
An excerpt from ?glm:
"For a binomial GLM prior weights are used to give
the _number of trials_ when the response is the
_proportion of successes_"
-Peter Ehlers
I'd appreciate any help you can provide.
Thanks
Brad
http://www.nabble.com/file/p25969499/Regressions%2Bwith%2BWeights.txt
Regressions+with+Weights.txt
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