BASELINE Statement

The PHREG Procedure

BASELINE Statement

BASELINE < OUT= SAS-data-set >< COVARIATES= SAS-data-set >
< 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 ( $x={\overline{z}}$ ) 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 time-dependent variable. The following list explains specifications in the BASELINE statement.

OUT=SAS-data-set

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=SAS-data-set

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, $\sqrt{ x'{\hat{V}} ({\hat{{\beta}}}) x }$
SURVIVAL: survivor function estimate ${\hat{S}}(t)=[{\hat{S}}_{0}(t)]^ { {\rm exp}(x'{\hat{{\beta}}}) }$
UPPER | U: upper confidence limit for the survivor function
XBETA: estimate of the linear predictor, $x'{\hat{{\beta}}}$

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 back-transforming 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 back-transforming 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 product-limit 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.

Chapter Contents
Previous
Next
Top