In the preceding syntax, variable
is a variable whose values determine the groups to be tested. The values for variable
can be formatted or unformatted. If variable
is a character or numeric variable, then the groups are defined by the unique values of the TEST variable. You can specify
only one variable in the TEST statement.
When you are comparing more than two survival curves, a generalized logrank test tells you whether the curves are significantly
different from each other, but it does not identify which pairs of curves are different. A multiplecomparison adjustment
of the pvalues for the paired comparisons retains the same overall probability of a Type I error as the Ksample test. Two types of paired comparisons can be made: comparisons between all pairs of curves and comparisons between
a control curve and all other curves. You use the DIFF=
option to specify the comparison type, and you use the ADJUST=
option to select a method of multiplecomparison adjustments.
Compared with the TEST statement in the LIFETEST procedure, the TEST statement in PROC ICLIFETEST is designed for comparing
survival between predefined groups. Unlike the LIFETEST procedure, PROC ICLIFETEST does not support a similar test for detecting
association with multiple covariates.
Table 62.2 summarizes the options available in the TEST statement.
Table 62.2: Options Available in the TEST Statement
Option

Description

Homogeneity Tests

NODETAIL

Suppresses printing the test statistic and covariance matrix

NOTEST

Suppresses all tests

OUTSCORE=

Names an output data set to contain the scores derived from the permutation form of the generalized logrank test

TREND

Requests a trend test

WEIGHT=

Specifies tests that correspond to various weight functions

Multiple Comparisons

ADJUST=

Requests a multiplecomparison adjustment

DIFF=

Specifies the type of differences to consider

You can specify the following options in the TEST statement after a slash ().

ADJUST=method

specifies the multiplecomparison method to use for adjusting the pvalues of the paired tests. For mathematical details, see the section MultipleComparison Adjustments; also see Westfall et al. (1999). You can specify the following adjustment methods:

BONFERRONI
BON

applies the Bonferroni correction to the raw pvalues.

DUNNETT

performs Dunnett’s twotailed comparisons of the control group to all other groups. PROC ICLIFETEST uses the factoranalytic
covariance approximation that is described in Hsu (1992) and identifies the adjustment in the results as "DunnettHsu." ADJUST=DUNNETT is incompatible with DIFF=
ALL.

SCHEFFE

performs Scheffé’s multiplecomparison adjustment.

SIDAK

applies the Šidák correction to the raw pvalues.

SMM
GTE

performs the paired comparisons based on the studentized maximum modulus test.

TUKEY

performs the paired comparisons based on Tukey’s studentized range test. PROC ICLIFETEST uses the approximation that is described
in Kramer (1956) and identifies the adjustment as "TukeyKramer" in the results. ADJUST=TUKEY is incompatible with DIFF=
CONTROL.

SIMULATE <(simulateoptions)>

computes the adjusted pvalues from the simulated distribution of the maximum or maximum absolute value of a multivariate normal random vector. The
simulation estimates q, the true quantile, where is the value of the ALPHA= simulateoption.
The number of samples for the simulation adjustment is set so that the tail area for the simulated q is within a certain accuracy radius of , with an accuracy confidence of %. In equation form,
where is the simulated q and F is the true distribution function of the maximum; for more information, see Edwards and Berry (1987). By default, = 0.005 and = 0.01, so the tail area of is within 0.005 of 0.95 with 99% confidence.
You can specify the following simulateoptions:

ACC=value

specifies the target accuracy radius of a % confidence interval for the true probability content of the estimated quantile. By default, ACC=0.005.

ALPHA=value

specifies the value for estimating the quantile. The default value is the ALPHA= value in the PROC ICLIFETEST statement, or 0.05 if that option is not specified.

EPS=value

specifies the value for a % confidence interval for the true probability content of the estimated quantile. The default value for the accuracy confidence is 99%, corresponding to EPS=0.01.

NSAMP=n

specifies the sample size for the simulation. By default, n is set based on the values of the target accuracy radius and accuracy confidence % for an interval for the true probability content of the estimated quantile. With the default values for , , and (0.005, 0.01, and 0.05, respectively), by default NSAMP=12604.

REPORT

specifies that a report of the simulation be displayed, including a listing of the parameters, such as , , and , in addition to an analysis of various methods of estimating or approximating the quantile.

SEED=number

specifies an integer used to start the pseudorandom number generator for the simulation. If you do not specify a seed, or
if you specify a value less than or equal to 0, the seed is generated by default from reading the time of day from the computer’s
clock.

DIFF=ALL  CONTROL<(’string’ <…, ’string’>)>

specifies which pairs of survival curves to consider for the multiple comparisons. You can specify the following values:

ALL

requests all paired comparisons.

CONTROL <(’string’ <…’string’>)>

requests comparisons of the control survival curve with all other survival curves. To specify the control curve, you specify
the quoted strings of formatted values that represent the curve in parentheses. For example, if CELL=LARGE identifies the
control group, you specify
DIFF=CONTROL('large')
If more than one variable is used to identify the curves (for example, if CELL=LARGE and SEX=F represent the control), you
specify
DIFF=CONTROL('large' 'F')
The order of the quoted strings should correspond to the order of the TEST variable. If no string is specified as the control, the first group value is used.
By default, DIFF=ALL unless you specify ADJUST=
DUNNETT, in which case DIFF=CONTROL.

NODETAIL

suppresses the display of the generalized logrank statistics and the corresponding covariance matrices. If you specify the
TREND option, the display of the scores for computing the trend test is suppressed.

NOTEST

suppresses the Ksample tests, stratified tests, and trend tests.

OUTSCORE=SASdataset
OUTSC=SASdataset

creates an output SAS data set to contain subject scores that are derived from a permutation form of the generalized logrank
statistic. For more information about the contents of the OUTSCORE= data set, see the section OUTSCORE= Data Set.

TREND

computes the trend test for the null hypothesis that the survival rates are the same for the groups versus an ordered alternative.
If the TEST variable is numeric, the unformatted values of the variable are used as the scores; otherwise, the scores are
in the order of the strata. For more information, see the section Trend Tests.

WEIGHT=testrequest  (testrequest <…testrequest>)

requests weights to be applied to the generalized logrank statistics to perform various tests. For more information about
the various weight functions that the ICLIFETEST procedure supports, see the section Generalized LogRank Statistic.
You can specify the following testrequests: