Probit Regression Vs Logistic Regression. Mar 04 2019 The logit model uses something called the cumulative distribution function of the logistic distribution. Logistic regression is a statistical model that in its basic form uses a logistic function to model a binary dependent variable although many more complex extensions exist.
The difference between Logit and Probit models lies in the use of Link function. Different link functions logit vs. Stokes Davis and Koch 1995 provide substantial discussion of these procedures particularly the use of the LOGISTIC and CATMOD procedures for statistical modeling.
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Probit assumes a Gaussian normal distribution. Logistic Regression Assumptions 1. This procedure includes a CLASS statement. Stokes Davis and Koch 1995 provide substantial discussion of these procedures particularly the use of the LOGISTIC and CATMOD procedures for statistical modeling.
