Simulate a survival data with the following specifications:
- Event time T follows an exponential distribution with a mean of 40
- Censoring time Tc follows an exponential distribution with a mean of 25
- Generate 500 observations, with censoring flag indicating whether censoring happened before events.
i. From your simulated data, what’s the percent of censoring?
ii. What do you think the percent of censoring should be? Show your calculation or reasoning.
iii. Consider the censored survival time in the variable ‘time’. What’s the median survival time? What’s the mean survival time? Paste your SAS code below, keeping the editing style (color, font, etc).Use the sample code to complete the part that is attached:
data survData;
lambdat = 0.02; *baseline hazard;
lambdac = 0.04; *censoring hazard;
do i = 1 to 100;
t = RANEXP(12345)/lambdat; * time of event;
c = RANEXP(67890)/lambdac; * time of censoring;
time = min(t, c); * which happens first?;
censored = (c < t); * censored when the censoring hapapened before event;
output;
end;
drop i lambda:;
run;
proc freq data=SurvData;
tables censored ;
run;
proc univariate data=survData;
histogram T C;
run;
data survData;
lambdat = 0.02; *baseline hazard;
lambdac = 0.04; *censoring hazard;
do i = 1 to 100;
t = RANEXP(12345)/lambdat; * time of event;
c = RANEXP(67890)/lambdac; * time of censoring;
time = min(t, c); * which happens first?;
censored = (c < t); * censored when the censoring hapapened before event;
output;
end;
drop i lambda:;
run;
proc freq data=SurvData;
tables censored ;
run;
proc univariate data=survData;
histogram T C;
run;
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