Programming the statistical procedures from SAS

How do I use Proc Iclifetest to obtain a 95% bootstrap confidence interval?

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How do I use Proc Iclifetest to obtain a 95% bootstrap confidence interval?

Hello, I am trying to use proc iclifetest statement to obtain KM estimates and their 95% pointwise bootstrap confidence interval. I have already been able to obtain my KM estimates survival curve using proc lifetest. The problem is my code is not working based on the options given by SAS for proc iclifetest and there are no examples of using this procedure to obtain the bootstrap confidence interval, only specified options. 

 

My code:

proc iclifetest data=A  bootstrap(nboot=500) (seed=0);
time survival*died(0);
run;

 

This is the code I used to produce my survival curve: 

 

proc lifetest data=A(where=(B<>'High')) plot=survival(cl cb=hw);
time survival*died(0);
run;

 

Any help is appreciated. Thank you. 


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‎02-25-2016 09:59 AM
SAS Super FREQ
Posts: 3,537

Re: How do I use Proc Iclifetest to obtain a 95% bootstrap confidence interval?

The Getting Started example from the procedure's documentation is worth reading.

Put all bootstrap options inside the paentheses:

proc iclifetest data=A  bootstrap(nboot=500 seed=123) plots=(survival);

 

The TIME statement requires that you specify two variables in parentheses:

time (Left, Right);

The first variable gives the left-hand bounds and the second variable gives the right-hand bounds of the interval for the event, with missing values used to represent censored values.

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Solution
‎02-25-2016 09:59 AM
SAS Super FREQ
Posts: 3,537

Re: How do I use Proc Iclifetest to obtain a 95% bootstrap confidence interval?

The Getting Started example from the procedure's documentation is worth reading.

Put all bootstrap options inside the paentheses:

proc iclifetest data=A  bootstrap(nboot=500 seed=123) plots=(survival);

 

The TIME statement requires that you specify two variables in parentheses:

time (Left, Right);

The first variable gives the left-hand bounds and the second variable gives the right-hand bounds of the interval for the event, with missing values used to represent censored values.

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