Hi AllStaters
I need some help on a survival simulation I am conducting.
I generate survival data using an exponential distribution for event and censoring times
event_times=exp(lamda_e)
censored_times=exp(lambda_c)
Then the minimum between the two is used and event or censoring is dependent on which is the minimum. This is considered the truth (similar to one group in a trial of time to event outcome)
I then generate another variable for loss to follow-up times using lost_times=exp(lamba_l).
I then use imputaion methods to predict whether the lost time was either a event or censored time. Once I have completed this, I would like to compare this predicted survival function to the "truth" and I am wondering what would be the best measure of bias??? Quantiles is not possible because the truth data may not have exact 0.25, 0.5 and 0.75 times.
Any help wiill be appreciated. Thanks
sameer
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