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 ...

This is a preview. Log in through your library . Abstract Quantal bioassay experiments relate the amount or potency of some compound; for example, poison, antibody, or drug to a binary outcome such as ...

Whenever I update The Capital Spectator Economic Trend Index (CS-ETI), as I did last week, someone usually asks how to interpret the data. In particular, how should we translate CS-ETI’s raw numbers ...

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 ...

• Background and Aims Most current thermal-germination models are parameterized with subpopulation-specific rate data, interpolated from cumulative-germination-response curves. The purpose of this ...

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 ...