Probit regression is very similar to logistic regression and the two techniques typically give similar results. Probit regression tends to be used most often with finance and economics data, but both ...

Equicorrelated binary observations are modelled using a multivariate probit regression model. Log likelihood derivatives are reduced to simple linear combinations of equicorrelated multivariate normal ...

An examination of socioeconomic disparities in cervical cancer screening across ethnic groups in the United States using concentration indices and probit regression analyses. Objectives: Our aim is to ...

Probit ("probability unit") regression is a classical machine learning technique that can be used for binary classification -- predicting an outcome that can only be one of two discrete values. For ...