New answers tagged overdispersion
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Accounting for overdispersion in binomial glm using proportions, without quasibinomial
This is an old question, but seeing as I just came across it and it was a top hit for my search, I'll offer another solution. Use a beta-binomial regression model!
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Why do I get different standard errors when i group the data before fitting a Quasi-Poisson GLM for counts with an offset = log(population)?
I found an answer to this question here: https://doi.org/10.1515/ijb-2020-0079. Essentially, grouping the data has no effect on coefficients but changes the standard error (upwards for overdispersed ...
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Generalized linear (mixed) model, binomial - help!
Regarding your second question, Is it ok to present these proportion plots, I would say yes, this is ok, but your plot is missing error bars. As you may know, most journal editors now ask for a ...
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Why do I get different standard errors when i group the data before fitting a Quasi-Poisson GLM for counts with an offset = log(population)?
I think the problem is that your ungrouped data don't fit the model.
If you divided the 24795 people in the first grouped record into 45 equal chunks of 551 before recording the response you would not ...
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What does the dispersion parameter mean in negative binomial regression?
I find it useful to verify these things empirically via simulation.
You can parametrized the negative binomial distribution via the mean number of successes at each trial and the dispersion (as ...
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