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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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How to deal with bias caused by data collected with different methods on a GLM?
I have two datasets from different years (2020 and 2021) that I needed to merge because my sample was too small. I'm investigating which morphological features (sex, age, weight, fat reserves and musc …