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Contents

Purpose

The %CIF macro implements nonparametric methods for estimating cumulative incidence functions with competing risks data. The macro can also be used to test the hypothesis that cumulative incidence functions are identical across groups.

History

Version	Update Notes
1.0	Initial version of %CIF macro (March 2012)

Requirements

The %CIF macro requires Base SAS and SAS/IML in SAS 9.2 or later releases. SAS/GRAPH is also required in SAS 9.2.

Usage

%CIF Macro

Follow the instructions in the Downloads tab of this sample to save the %CIF macro definition. Before calling the %CIF macro, specify the following %INC statement in your SAS program or in the SAS editor window to define the macro and make it available for use. In the %INC statement, replace the text within quotes with the location where you saved the %CIF macro definition file on your system.

%inc "<location of your file containing the CIF macro>";

Following this statement, you call the %CIF macro using the following syntax:

%CIF "<list of macro parameters separated by commas>";

The following parameters may be listed within parentheses in any order, separated by commas. Only the DATA=, OUT=, TIME=, and STATUS= parameters are required; the other parameters are optional. The parameters are defined as follows:

DATA=SAS-data-set
     specifies the SAS data set that contains the data to be analyzed.

OUT=SAS-data-set
     specifies an output data set with estimates of cumulative incidence functions and confidence limits.
     If you omit the OUT=parameter, the output data set is created with a default name of cifEstimate.

TIME=variable
     specifies the name of the failure-time variable.

STATUS=variable
     specifies the name of the numeric variable whose values indicate whether an observation corresponds to the event of interest, 
     the competing events, or is censored.

EVENT=(list)
     specifies values of the STATUS= variable that identify failure times from a cause of interest. Use blanks to separate multiple values. 
     The default value is 1.

CENSORED=(list)
     specifies values of the STATUS= variable that identify censored observations. Use blanks to separate multiple
     values. The default value is 0.

GROUP=variable
     specifies the name of the variable that defines the groups for comparison.

STRATA=variable
     specifies the name of the variable that defines the strata for a stratified test; see Gray (1988).

ALPHA=value
    specifies the level of the pointwise confidence intervals. The value must be between 0 and 1. The default is 0.05.

PHO=value
    specifies the power of the weight function in the test; see Gray (1988). The value must be between 0 and 1. The default is 0.

SE=value
    specifies a method for computing the standard error of the cumulative incidence function. Specify SE=1 for the delta method, 
    and specify SE=2 for the counting process method.

TITLE=value
    specifies the first title for the cumulative incidence function plot. Do not use quotation marks.

TITLE2=value
    specifies the second title for the cumulative incidence function plot. Do not use quotation marks.

OPTIONS=keyword
    specifies one or more of the following keywords separated by blanks:
•	NOPLOT suppresses plots of the cumulative incidence functions.
•	PLOTCL plots the pointwise confidence limits for cumulative incidence functions.
•	NOCIFEST suppresses the table that contains the estimated cumulative incidence functions.
•	NOTEST suppresses the test for equality for cumulative incidence functions among groups.

Details

Estimation of cumulative incidence functions

For competing risks data, the cumulative incidence function is the cumulative probability of failure from a specific cause over time.

Test for equality of cumulative incidence functions survival curves among groups

When you compare treatment effects on the cumulative incidence function, the null hypothesis H_0 is that the cumulative incidence functions are identical across treatment groups. The %CIF macro implements a test due to Gray (1988). See Lin, So, and Johnston (2012) for more discussion.

References

Lin, G., So, Y., and Johnston, G. (2012), “Analyzing Survival Data with Competing Risks Using SAS® Software," Proceedings of the SAS® Global Forum 2012 Conference, Cary, NC: SAS Institute Inc.

 

Gray, R. (1988), “A Class of K-Sample Tests for Comparing the Cumulative Incidence of a Competing Risk,” The Annals of Statistics, 16, 1141–1154.

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These sample files and code examples are provided by SAS Institute Inc. "as is" without warranty of any kind, either express or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Recipients acknowledge and agree that SAS Institute shall not be liable for any damages whatsoever arising out of their use of this material. In addition, SAS Institute will provide no support for the materials contained herein.

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These sample files and code examples are provided by SAS Institute Inc. "as is" without warranty of any kind, either express or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose. Recipients acknowledge and agree that SAS Institute shall not be liable for any damages whatsoever arising out of their use of this material. In addition, SAS Institute will provide no support for the materials contained herein.

Example

%inc "C:.../cif.sas";

%inc "C:.../bmtdata.sas";

%CIF(DATA=bmt,TIME=Ftime,STATUS=Status,EVENT=1,CENSORED=0,GROUP=Diagnosis);

Results

• Right-click %CIF macro Version 1.0
• Select "Save target as"
• Select save as type "All Files"
• Name file cif.sas

• Right-click "bmtdata.sas"
• Select "Save target as"
• Select save as type "All Files"
• Name file bmtdata.sas

Operating System and Release Information