Hello,
I am using a competing risk regression (Fine and Gray) model to understand patient characteristics associated with major cardiac events (MCE) after organ transplantation. The outcome is MCE and I am using non-MCE death as a competing risk. A single variable included in my final (pack-years smoked) contains missing data and I would like to run the model using multiple imputation for this variable. Thus far, my code is:
I would like to plot the CIF by diabetes status:
Easy to do in the non-imputed data, but in the imputed data, I receive an error: "last estimates not found r(301);
Any advice on how to remedy this is appreciated!
In addition to plotting the CIF, I would love to generate point estimates of CIF with 95% confidence intervals at specific follow up times (ie: 12 months, 60 months and 120 months after organ transplant).
Finally, is there a way to perform the Gray test to determine if the cumulative incidence of MCE differs among the different exposures (ie: diabetes status)?
Thank you for any help you can offer.
Giorgio
I am using a competing risk regression (Fine and Gray) model to understand patient characteristics associated with major cardiac events (MCE) after organ transplantation. The outcome is MCE and I am using non-MCE death as a competing risk. A single variable included in my final (pack-years smoked) contains missing data and I would like to run the model using multiple imputation for this variable. Thus far, my code is:
Code:
mi stset cohort_end1, id( study_id) fail( comp_risk ==1 ) origin( cohort_date) enter(cohort_date)
Code:
mi estimate, hr: stcrreg i.diabetes i.race i.gender age pack_years i.htn year_transplant, compete(comp_risk==2)
Code:
stcurve, cif at1(diabetes=0) at2(diabetes=1) at3(diabetes =2)
Any advice on how to remedy this is appreciated!
In addition to plotting the CIF, I would love to generate point estimates of CIF with 95% confidence intervals at specific follow up times (ie: 12 months, 60 months and 120 months after organ transplant).
Finally, is there a way to perform the Gray test to determine if the cumulative incidence of MCE differs among the different exposures (ie: diabetes status)?
Thank you for any help you can offer.
Giorgio
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