1. The probit model has been around longer than the logit model. 2. Ordered logit and ordered probit models are derived under this concept. 3. The coefficients obtained from the logit and probit model are fairly close. 4. The canonical specification for this relationship is a probit regression of the form 5. All the discussion above is mainly about the probit model. 6. In this case, the multinomial probit or multinomial logit technique is used. 7. Logistic regression and probit models are used when the dependent variable is binary. 8. Probit models offer an alternative to logistic regression for modeling categorical dependent variables.9. Probit models are popular in social sciences like economics.10. The probit model assumes that the error term follows a standard normal distribution.
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