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  • Cumulative Incidence with Confidence Intervals when using IPTW

    Dear Stata users,

    I'm doing a time to event analysis with inverse probability of treatment weights(IPTW) estimated with propensity scores from a multivariate logistic regression model.

    I have estimated a weight adjusted hazard ratio and would like estimate a cumulative incidence at specific time points (day 90 and year 5) with 95% confidence intervals.

    I'm also doing a competing risk analysis with the same method.

    Below is the code I would use:

    stset timevar [pweights=iptw], failure(cause==1) exit(time 1826.25)
    sts list, at(90 1826.26)


    This gives me estimates of cumulative incidence; however, not a 95% CI. To my knowledge the confidence intervals was removed in Stata 10 (see following link: http://www.stata.com/statalist/archi.../msg00124.html ).
    Do any of you have experience with obtaining the confidence intervals for cumulative incidence in Stata weight the data are weighted?


    In the competing risk analysis I use the following code:

    stset timevar [pweights=iptw], failure(cause==1) exit(time 1826.25)
    stcompet ci = ci se = se, compet1(2)


    When I use the stcompet command it changes cumulative incidence estimates compared to when I not include weights in the stset command, but are the SE obtained by this method valid when weights are used? In the help file for stcompet weights are not mentioned.
    I'm using Stata 14.2 for Mac.


    Soren Christiansen
    Research year student
    Department of Clinical Epidemiology
    Aarhus University Hospital



    Last edited by Soren Christiansen; 09 Nov 2016, 12:23.

  • #2
    Dear Stata users,
    I am facing the exact problem above: when using inverse probability of treatment weights (IPTW) estimated with propensity scores, the "sts list" command gives the estimates of cumulative incidence, but not the respective 95% CI.
    Is there a strategy to calculate these 95% CI? As Soren Christiansen pointed out, this is a recurrent but unaddressed problem.
    Thank you all a lot!

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