OUTROC= Data Set
The OUTROC= data set contains data necessary for producing the ROC curve.
the following variables:
Note that none of these statistics are affected by the bias-correction
method discussed in the "Classification Table" section.
An ROC curve is obtained by plotting _SENSIT_
For more information, see the section "Receiver Operating Characteristic Curves".
- any BY variables specified
- _STEP_, the model step number. This variable is not
included if model selection is not requested.
- _PROB_, the estimated probability of an event.
These estimated probabilities serve as cutpoints
for predicting the response. Any observation with
an estimated event probability that exceeds or
is predicted to be an event; otherwise, it is predicted
to be a nonevent. Predicted probabilities
that are close to each other are grouped together, with the
maximum allowable difference between the largest and
smallest values less than
a constant that is specified by the ROCEPS=
option. The smallest
estimated probability is used to represent the group.
- _POS_, the number of correctly predicted event responses
- _NEG_, the number of correctly predicted nonevent responses
- _FALPOS_, the number of falsely predicted event responses
- _FALNEG_, the number of falsely predicted nonevent responses
- _SENSIT_, the sensitivity, which is the proportion
of event observations that were predicted to have an event
- _1MSPEC_, one minus specificity, which is the proportion
of nonevent observations that were predicted to have an
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.