A probit model is a type of regression where the dependent variable is binary. It assumes that the underlying relationship between the outcome and the predictors can be represented by a standard normal cumulative distribution function. In other words, the probit model estimates the probability that a certain event (e.g., disease occurrence) happens, given a set of explanatory variables.
