The PROBIT Procedure

Model Specification

For a two-level response, the probability that the lesser response occurs is modeled by the probit equation as

p equals upper C plus left-parenthesis 1 minus upper C right-parenthesis upper F left-parenthesis bold x prime bold b right-parenthesis

The probability of the other (complementary) event is 1 – p.

For a multilevel response with outcomes labeled l Subscript i for i equals 1 comma 2 comma ellipsis comma k, the probability, p Subscript j, of observing level l Subscript j is as follows:

StartLayout 1st Row 1st Column p 1 2nd Column equals 3rd Column upper C plus left-parenthesis 1 minus upper C right-parenthesis upper F left-parenthesis bold x prime bold b right-parenthesis 2nd Row 1st Column p 2 2nd Column equals 3rd Column left-parenthesis 1 minus upper C right-parenthesis left-parenthesis upper F left-parenthesis a 2 plus bold x prime bold b right-parenthesis minus upper F left-parenthesis bold x prime bold b right-parenthesis right-parenthesis 3rd Row 1st Column Blank 2nd Column vertical-ellipsis 3rd Column Blank 4th Row 1st Column p Subscript j 2nd Column equals 3rd Column left-parenthesis 1 minus upper C right-parenthesis left-parenthesis upper F left-parenthesis a Subscript j Baseline plus bold x prime bold b right-parenthesis minus upper F left-parenthesis a Subscript j minus 1 Baseline plus bold x prime bold b right-parenthesis right-parenthesis 5th Row 1st Column Blank 2nd Column vertical-ellipsis 3rd Column Blank 6th Row 1st Column p Subscript k 2nd Column equals 3rd Column left-parenthesis 1 minus upper C right-parenthesis left-parenthesis 1 minus upper F left-parenthesis a Subscript k minus 1 Baseline plus bold x prime bold b right-parenthesis right-parenthesis EndLayout

Thus, for a k-level response, there are k – 2 additional parameters, a 2 comma a 3 comma ellipsis comma a Subscript k minus 1 Baseline, estimated. These parameters are denoted by Interceptj, j equals 2 comma 3 comma ellipsis comma k minus 1, in the output.

An intercept parameter is always added to the set of independent variables as the first term in the model unless the NOINT option is specified in the MODEL statement. If a classification variable taking on k levels is used as one of the independent variables, a set of k indicator variables is generated to model the effect of this variable. Because of the presence of the intercept term, there are at most k – 1 degrees of freedom for this effect in the model.

Last updated: December 09, 2022