OUTPUT Statement |
The OUTPUT statement creates a new SAS data set that contains statistics that are calculated for each observation unit. These statistics can include the estimated linear predictor () and its standard error, residuals, and influence statistics. In addition, this data set includes all the variables from the DATA= input data set.
Only score residuals are available in the OUTPUT data set if the model contains a time-dependent variable that is defined by means of programming statements.
The following list explains specifications in the OUTPUT statement:
names the output data set. If you omit the OUT= option, the OUTPUT data set is named by using the DATAn convention. See the section OUT= Data Set for the OUTPUT statement for more information.
specifies the number of subjects at risk at the observation time .
specifies the deviance residual . This is a transform of the martingale residual to achieve a more symmetric distribution.
specifies the martingale residual . The residual at the observation time can be interpreted as the difference over in the observed number of events minus the expected number of events given by the model.
specifies the Schoenfeld residuals. These residuals are useful in assessing the proportional hazards assumption.
specifies the score residuals. These residuals are a decomposition of the first partial derivative of the log likelihood. They can be used to assess the leverage that is exerted by each subject in the parameter estimation. They are also useful in constructing design-based variance estimators.
specifies the standard error of the estimated linear predictor, .
specifies the weighted number of subjects at risk at the observation time .