BASELINE Statement
 BASELINE < OUT= SASdataset ><
COVARIATES= SASdataset >
< keyword=name ... keyword=name > <
/options > ;
The BASELINE statement creates a new SAS data set that
contains the survivor function estimates at the event times
of each stratum
for every pattern of explanatory
variable values (x) given in the COVARIATES=
data set.
By default,
the data set also contains the survivor function estimates
corresponding to the
means of the explanatory variables () for
each stratum.
If you want only these estimates, you can omit
the COVARIATES= option.
No BASELINE
data set is created if the counting process style of input is used
or if the model contains a timedependent variable.
The following list explains specifications in the BASELINE statement.
 OUT=SASdataset

names the output BASELINE data set. If you omit the OUT= option, the
data set is created and given a default name using the DATAn
convention.
 COVARIATES=SASdataset

names the SAS data set containing the set of explanatory
variable values for which the survivor functions are estimated.
There must
be a corresponding variable in the COVARIATES= data set for each
explanatory variable in the final model.
 keyword=name

specifies the statistics included in the BASELINE data set and assigns
names to the new variables that contain the statistics. Specify a
keyword for each desired statistic (see the following list of
keywords), an equal sign, and the variable to contain the
statistic. The keywords and the corresponding statistics are

LOGLOGS
 log of the negative log of SURVIVAL

LOGSURV
 log of SURVIVAL

LOWER  L

lower confidence limit for the survivor function

STDERR

standard error of the survivor function estimate

STDXBETA

standard error of the estimated linear predictor,

SURVIVAL
 survivor function estimate

UPPER  U

upper confidence limit for the survivor function

XBETA
 estimate of the linear predictor,
The following options can appear in the BASELINE statement
after a slash (/).
 ALPHA=value

specifies the significance level of the confidence interval for
the survivor function.
The value must be between 0 and 1. The default is 0.05, which
results in a 95% confidence interval.
 CLTYPE=method

specifies the method used to compute the confidence limits
for S(t,z), the survivor function for a subject with a
fixed covariate vector z at event time t. The CLTYPE= option
can take the following values:
 LOG
 specifies that the confidence limits for log(S(t,z))
are to be computed using the normal
theory approximation.
The confidence limits for S(t,z) are obtained by backtransforming the
confidence limits for log(S(t,z)). The default is CLTYPE=LOG.
 LOGLOG
 specifies that the confidence limits for the log(log(S(t,z)))
are to be computed using normal theory approximation.
The confidence limits for S(t,z) are obtained by backtransforming
the confidence limits for log(log(S(t,z))).
 NORMAL
 specifies that the confidence limits for S(t,z) are to
be computed directly using normal theory approximation.
 METHOD=method

specifies the method used to compute the survivor function estimates.
The two available methods are
 CH  EMP
 specifies that the empirical cumulative hazard function estimate of
the survivor function is to be computed; that is, the survivor
function is estimated by exponentiating the negative
empirical cumulative hazard function.
 PL
 specifies that the productlimit estimate of the survivor
function is to be computed. The default is METHOD=PL.
 NOMEAN

excludes the survivor function estimates
corresponding to the sample means
of the explanatory variables.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.