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The PROBIT Procedure |

The OUTEST= data set contains parameter estimates and the log likelihood for the specified models. A set of observations is created for each MODEL statement specified. You can use a label in the MODEL statement to distinguish between the estimates for different MODEL statements. If you specify the COVOUT option, the OUTEST= data set also contains the estimated covariance matrix of the parameter estimates.

The OUTEST= data set is not created if there are any CLASS variables in any model. If created, this data set contains each variable used as a dependent or independent variable in any MODEL statement. One observation consists of parameter values for the model with the dependent variable having the value -1. If you specify the COVOUT option, there are additional observations containing the rows of the estimated covariance matrix. For these observations, the dependent variable contains the parameter estimate for the corresponding row variable. The following variables are also added to the data set:

- _MODEL_
- a character variable of length 8 containing the label
of the MODEL statement, if present, or blank otherwise
- _NAME_
- a character variable containing the name of the dependent
variable for the parameter estimates observations or
the name of the row for the covariance matrix estimates
- _TYPE_
- a character variable containing the type of
the observation, either PARMS for parameter
estimates or COV for covariance estimates
- _DIST_
- a character variable containing the
name of the distribution modeled
- _LNLIKE_
- a numeric variable containing the last
computed value of the log likelihood
- _C_
- a numeric variable containing the estimated
threshold parameter
- INTERCEPT
- a numeric variable containing the intercept parameter estimates and covariances

Any BY variables specified are also added to the OUTEST= data set.

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