Displayed Output
If you request the iteration history
(ITPRINT), PROC PROBIT displays
- the current value of the log likelihood
- the ridging parameter for the modified
Newton-Raphson optimization process
- the current estimate of the parameters
- the current estimate of the parameter C
for a natural (threshold) model
- the values of the gradient and
the Hessian on the last iteration
If you include CLASS variables, PROC PROBIT displays
- the numbers of levels for each CLASS variable
- the (ordered) values of the levels
- the number of observations used
After the model is fit, PROC PROBIT displays
- the name of the input data set
- the name of the dependent variables
- the number of observations used
- the number of events and the number of trials
- the final value of the log-likelihood function
- the parameter estimates
- the standard error estimates of the parameter estimates
- approximate chi-square test statistics for the test
If you specify the COVB or CORRB options, PROC PROBIT displays
- the estimated covariance matrix for the parameter estimates
- the estimated correlation matrix for the parameter estimates
If you specify the LACKFIT option, PROC PROBIT displays
- a count of the number of levels of the response and
the number of distinct sets of independent variables
- a goodness-of-fit test based on the Pearson chi-square
- a goodness-of-fit test based on the
likelihood-ratio chi-square
If you specify only one independent variable,
the normal distribution is used to
model the probabilities, and the response is binary,
PROC PROBIT displays
- the mean MU of the stimulus tolerance
- the scale parameter SIGMA of the stimulus tolerance
- the covariance matrix for MU, SIGMA, and the natural response
parameter C
If you specify the INVERSECL options, PROC PROBIT also displays
:::START=25:::
- the estimated dose along with the 95% fiducial
limits for probability levels 0.01 to 0.10,
0.15 to 0.85 by 0.05, and 0.90 to 0.99
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.