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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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Comparing average success rates of varying sample sizes

I have the following data frame: False True Total Cases Success % surgeon_id 0 1.0 0.0 1.0 0.000000 2 …
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