PROC PHREG Statement
 PROC PHREG < options > ;
You can specify the following options in the PROC PHREG statement.

COVOUT

adds the estimated covariance matrix of the parameter estimates
to the OUTEST= data set.
The COVOUT option has no effect unless the OUTEST= option is
specified.

DATA=SASdataset

names the SAS data set containing the data to be analyzed. If you
omit the DATA= option, the procedure uses the most recently
created SAS data set.

MULTIPASS

requests that PROC PHREG recalculate the values of the
variables defined by the programming statements
at each NewtonRaphson iteration instead of calculating
the variable values once and saving them in a
utility data set. This option has an effect only when the
model contains timedependent explanatory variables. It decreases
required disk space at the expense of increased execution time.

NOPRINT

suppresses all displayed output. Note that this option
temporarily disables the Output Delivery
System (ODS); see Chapter 14, "Using the Output Delivery System," for more information.

NOSUMMARY

suppresses the display of the event and censored observation
frequencies.

OUTEST=SASdataset

creates an output SAS data set that contains
estimates of the regression coefficients.
If you use the COVOUT option, the data set
also contains the estimated covariance
matrix of the parameter estimates.
The data set includes
 one variable for each explanatory variable in the
MODEL statement. In a forward, backward, or stepwise regression
analysis, if an explanatory variable is not included
in the final model, the corresponding parameter estimate and
covariances are set to missing.
 any BY variables specified
 _TIES_, a character variable of length 8 with four
possible values: BRESLOW, DISCRETE, EFRON, and EXACT.
These are the four values
of the TIES= option in the MODEL statement.
 _TYPE_, a character variable of length 8 with two possible
values: PARMS for parameter estimates or COV for covariance estimates
 _NAME_, a character variable of length 8
containing the name ESTIMATE for parameter estimates and the name for
each explanatory variable to label covariance estimates
 _LNLIKE_, a numeric variable containing the last computed
value of the log likelihood

SIMPLE

displays simple descriptive statistics (mean,
standard deviation, minimum, and maximum) for each explanatory
variable in the MODEL statement.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.