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A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "general linear model" which extends the ordinary linear model to general covariance structure and multivariate response.)

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Binomial GLM in R: Is there any overdispersion test, like AER package?

I have (mydata) as example: mydata <- read.csv("https://stats.idre.ucla.edu/stat/data/binary.csv") ## view the first few rows of the data head(mydata) mydata$rank <- factor(mydata$rank) mylogit <- gl …
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Binomial GLM in R: Is there any overdispersion test, like AER package?

By Ben Bolker and others (https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#overdispersion) overdisp_fun <- function(model) { rdf <- df.residual(model) rp <- residuals(model,type="pearso …
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