
ALPHA=

specifies the level for the % confidence intervals for the survival functions. For example, ALPHA=0.05 requests 95% confidence limits. By default, ALPHA=0.05.

ALPHAQT=

specifies the level for the % confidence intervals for the quartiles of the survival time. For example, ALPHAQT=0.05 requests a 95% confidence interval.
By default, ALPHAQT=0.05.

BOOTSTRAP <(options)>
BOOT <(options)>

performs simple bootstrap sampling and computes bootstrap standard errors of nonparametric survival estimates. You can specify
the following suboptions to control how the bootstrap samples are generated:

NBOOT

specifies the number of bootstrap samples to be generated. The default value is 1,000.

SEED

specifies the seed to generate bootstrap samples. The default seed is selected randomly.

CONFTYPE=ASINSQRT  LINEAR  LOG  LOGLOG

specifies the transformation to be applied to to obtain pointwise confidence intervals for the survival function in addition to the confidence intervals for the quartiles
of the survival times. You can specify the following keywords:
 ASINSQRT

specifies the arcsine–square root transformation,
 LOGLOG

specifies the log–log transformation,
This is also referred to as the log cumulative hazard transformation, because it applies the log transformation to the cumulative
hazard function. Collett (1994) and Lachin (2000) call it the complementary loglog transformation.
 LINEAR

specifies the identity transformation,
 LOG

specifies the log transformation,
 LOGIT

specifies the logit transformation,
By default, CONFTYPE=LOGLOG.

DATA=SASdataset

names the SAS data set that PROC ICLIFETEST reads. By default, the most recently created SAS data set is used.

IMPUTE <(options)>
IM <(options)>

specifies details for multiple imputations. You can specify the following two suboptions to control how the samples are generated:

NIMSE

specifies the number of imputation samples to be generated for computing standard errors of the survival estimates. The default
value is 1,000.

NIMTEST

specifies the number of imputation samples to be generated for estimating the covariance matrix of the generalized logrank
statistic. The default value is 1,000.

SEED

specifies the seed to generate imputation data sets. The default seed is selected randomly.

ITHISTORY

prints the iteration history of the nonparametric estimation, including the log likelihood, the probability estimate that
is associated with each Turnbull interval, and whether the EM or ICM method is used for each iteration.

MAXITER=n
MAXIT=n

specifies the maximum number of iterations for estimating the survival function. The default value depends on the estimation
method as follows:

EMICM method: 200

ICM method: 200

Turnbull method: 500
Note that you specify the method with the METHOD= option.

MAXTIME=value

specifies the maximum value of the time variable that is allowed in plots so that outlying points do not determine the scale
of the time axis of the plots. This option affects only the way in which plots are displayed and has no effect on any calculations.

METHOD=TURNBULL  ICM  EMICM

specifies the method to be used for computing survival function estimates. You can specify the following:

TURNBULL
EM

requests that the Turnbull method be used to estimate the survival function.

EMICM

requests that the EMICM algorithm be used to estimate the survival function.

ICM

requests that the iterative convex minorant algorithm be used to estimate the survival function.
By default, METHOD=EMICM.

MISSING

allows missing values to be a stratum level or a valid group for the variables that are specified in the STRATA and TEST statements.

NOPRINT

suppresses the display of output. This option is useful when only an output data set is needed. It temporarily disables the
Output Delivery System (ODS); for more information about ODS, see Chapter 20: Using the Output Delivery System.

NOSUMMARY

suppresses the summary table of the number of censored and uncensored values.

OUTSURV=SASdataset
OUTS=SASdataset

creates an output SAS data set to contain the estimates of the survival function and corresponding confidence limits for all
strata. For more information about the contents of the OUTSURV= data set, see the section OUTSURV= Data Set.

PLOTS<(globalplotoptions)>=plotrequest <(options)>
PLOTS<(globalplotoptions)>=(plotrequest <(options)> <…plotrequest <(options)>>)

controls the plots that are produced by using ODS Graphics. When you specify only one plotrequest, you can omit the parentheses around it. Here are some examples:
plots=none
plots=(survival(cl) logsurv)
plots(only)=hazard
ODS Graphics must be enabled before plots can be requested. For example:
ods graphics on;
proc iclifetest plots=survival;
time (Left,Right);
run;
ods graphics off;
For more information about enabling and disabling ODS Graphics, see the section Enabling and Disabling ODS Graphics in Chapter 21: Statistical Graphics Using ODS.
If ODS Graphics is enabled but you do not specify the PLOTS= option, then by default PROC ICLIFETEST produces a plot of the
estimated survival functions.
You can specify the following globalplotoption:

ONLY

specifies that only the specified plots in the list be produced; otherwise, the default survival function plot is also displayed.
You can specify the following plotrequests and their options:

ALL

produces all appropriate plots. Specifying PLOTS=ALL is equivalent to specifying PLOTS=(SURVIVAL LOGSURV LOGLOGS HAZARD).

HAZARD <(hazardoptions)>
H <hazardoptions>

plots the Kernelsmoothed hazard functions.
You can specify the following hazardoptions.

BANDWIDTH=value  numericlist  RANGE(lower,upper)
BW=

specifies the bandwidth for kernelsmoothed estimation of the hazard function. You can specify one of the following:

value

sets the bandwidth to the given value.

numericlist

selects the bandwidth from the specified numericlist that minimizes the mean integrated squared error.

RANGE(lower,upper)

selects from the interval (lower, upper) the bandwidth that minimizes a cross validation pseudolikelihood function. PROC ICLIFETEST uses the golden section search
algorithm to find the minimum. If the interval contains more than one local minimum, there is no guarantee that the local
minimum that the algorithm finds is also the global minimum.
For more information about the cross validation pseudolikelihood function, see the section KernelSmoothed Estimation. By default, BANDWIDTH= RANGE(0.1b,0.25b), where ; is the left boundary of the first Turnbull interval; and is the right boundary of the last Turnbull interval if it is finite or the left boundary of that interval multiplied by otherwise.

SAMPLING=LEAVEONE  RANDOM

specifies how to partition the data set to form cross validation groups. You can specify the following values:

LEAVEONE

partitions the data set into leaveoneout subsets.

RANDOM

randomly assigns observations to cross validation groups with equal probabilities.
By default, SAMPLING=RANDOM.

GRIDL=number

specifies the lower grid limit for the kernelsmoothed estimate. The default value is the time origin.

GRIDU=number

specifies the upper grid limit for the kernelsmoothed estimate. The default value is the maximum input boundary value.

KERNEL=kerneloption

specifies the kernel to be used. You can specify the following values:

BIWEIGHT
BW

uses the following kernel:

EPANECHNIKOV
E

uses the following kernel:

UNIFORM
U

uses the following kernel:
By default, KERNEL=EPANECHNIKOV.

CVFOLD=number

specifies the number of cross validation groups. This option is applicable only when SAMPLING=RANDOM. The default number is either 5 or the sample size, whichever value is less.

CVGRID=number

specifies the number of grid points to use in determining the cross validation pseudolikelihood. By default, CVGRID=51.

HGRID=number

specifies the number of grid points for discretizing the smoothed hazard function. By default, HGRID=101.

LOGLOGS
LLS

plots the log of the negative log of the estimated survival function versus the log of time.

LOGSURV
LS

plots the negative log of the estimated survival function versus time.

NONE

suppresses all plots.

SURVIVAL <(CL  FAILURE  NODASH  STRATA  TEST)>
S <(CL  FAILURE  STRATA  TEST)>

plots the estimated survival function. You can customize the display by specifying the following values:

CL

displays pointwise confidence limits for the survival function.

FAILURE
F

changes all the displays for survival function to those for the failure function. For example, if you specify both the FAILURE
and CL options, the plot displays the failure curves in addition to pointwise confidence limits for the failure function.

NODASH

suppresses the plotting of dashed lines as linear interpolations for the Turnbull intervals.

STRATA=INDIVIDUAL  OVERLAY  PANEL

specifies how to display the survival or failure curves for multiple strata. This option has no effect if there is only one
stratum. You can specify one of the following values:

INDIVIDUAL
UNPACK

requests that a separate plot be displayed for each stratum.

OVERLAY

requests that the survival or failure curves for the strata be overlaid on the same plot.

PANEL

requests that separate plots for the strata be organized into panels of two or four plots, depending on the number of strata.
By default, STRATA=OVERLAY.

TEST

displays the pvalue for a Ksample test that is specified in the TEST statement.

SHOWTI

presents the survival estimates in terms of Turnbull intervals.

SINGULAR=value

sets the tolerance for testing the singularity of the covariance matrix of test statistics.

TOLLIKE=value

sets the loglikelihood convergence criterion for the estimation algorithm. The default value depends on the estimation method as follows:

EMICM method:

ICM method:

Turnbull method: