# Comparing Binomial Generalized Linear Models

Comparing Binomial Generalized Linear Models

Generalized linear models are models of the form =(+++…), where is an invertible function called the link function and the are basis functions of one or more predictor variables. The term +++… is linear in the and is referred to as the linear predictor. The value is the predicted response for the observed response , and the are assumed to be independent observations from the same exponential family of distributions. When the exponential family is the binomial family, the success probability is modeled.

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This Demonstration fits binomial models with various common link functions. Check the boxes next to the named link functions to fit models with those links. Select a linear predictor to choose the argument of in the model. The linear predictors are taken to be polynomials in a single predictor variable , so for instance, with a quadratic linear predictor, the model is +x+.

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Mouse over a fitted curve to see the functional form of the model. The residual deviances for the models are included in a table for comparison.