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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.)

3 votes

Why is a logistic regression model using glm() different from a linear model with a logit tr...

In addition to Dave's answer, I think this has been already addressed in: What is the difference between logit-transformed linear regression, logistic regression, and a logistic mixed model? My sugges …
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