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Sample 45997: Nonparametric Estimation and Comparison of Cumulative Incidence Functions with Competing Risks Data (%CIF Macro)
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Contents
Purpose | History | Requirements | Usage | Details | ReferencesNOTE: Beginning with SAS/STAT® 14.1 and in SAS 9.4 TS1M3, the functionality of this macro has been updated and added to the LIFETEST Procedure. For details, see the LIFETEST documentation.
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. Beginning in SAS/STAT 12.1 (SAS9.3 TS1M2), the CIF macro is available via the AUTOCALL library and does not need to be downloaded. Because the macro is in the AUTOCALL library, it is already defined in any SAS session and it can be invoked at any time.
History
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Version Update Notes 1.0 Initial version of %CIF macro (March 2012)
Requirements
- The %CIF macro requires SAS 9.3 TS1M2 and SAS/IML®.
Usage
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%CIF Macro
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 counting process method, and specify SE=2 for the delta method. The default is SE=1. 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
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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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