Generalized linear modelsA generalized linear model (GLM) is a generalization of the linear models by allowing the linear model to be related to the response variable via a link function and an error distribution other than a normal distribution. The unknown model parameters are estimated using maximum-likelihood estimation.

Type	Description
Logit / Logistic	Fit a model to a binary response variable expressed by the logit link function (log odds ratio) and binomial error distribution. Note: This model is very common as the parameter estimates can be interpreted as the log-odds or back transformed into an odds ratio.
Probit	Fit a model to a binary response variable expressed by the probit function and binomial error distribution.