+ Reply to Thread
Results 1 to 2 of 2

Thread: Simulation of remission and after remission times under specific conditions

  1. #1
    Points: 4,825, Level: 44
    Level completed: 38%, Points required for next Level: 125

    Posts
    40
    Thanks
    8
    Thanked 0 Times in 0 Posts

    Simulation of remission and after remission times under specific conditions




    This is basically a data generation problem.

    Say, t is an exponential lifetime with mean two years. tr is the remission time and ts is the after remission time. So, t=tr+ts. I need to simulate these quantities for 100 patients. Now in real life, usually when tr is smaller, that is when the patients remit quickly, their after remission time ts are longer (so that the lifetimes t are also longer). When tr are longer, that is the patients remit slowly, their after remission times ts are shorter.

    One thing is known that the distribution of the lifetimes, t is exponential with mean two years. I don't have any information about their exact relationship but I know, this is the scenario in real life. I need to simulate data under this scenario because I want to see the performance of an estimator under these conditions. So any feasible assumption regarding how they are correlated is absolutely okay for me. But I cannot understand how to generate data from the above mentioned scenario. If some sort of randomness can be put along with maintaining the conditions, that will be great!

    Your suggestion will be a great help.

  2. #2
    TS Contributor
    Points: 22,410, Level: 93
    Level completed: 6%, Points required for next Level: 940

    Posts
    3,020
    Thanks
    12
    Thanked 565 Times in 537 Posts

    Re: Simulation of remission and after remission times under specific conditions


    It seems that you always need to have more assumption on the distributions of either t_s or t_r.

    One very naive way I could think of is that first you simulate the exponential distributed t.

    Next you need to assign a distribution with support (0, t), e.g. t\text{Uniform}(0, 1) or t\text{Beta}(a, b) for let say t_r. Subsequently you can obtain t_s = t - t_r.

+ Reply to Thread

           




Tags for this Thread

Posting Permissions

  • You may not post new threads
  • You may not post replies
  • You may not post attachments
  • You may not edit your posts






Advertise on Talk Stats