Constrained parametric model for simultaneous inference of two cumulative incidence functions
Version of Record online: 23 OCT 2012
© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Volume 55, Issue 1, pages 82–96, January 2013
How to Cite
Shi, H., Cheng, Y. and Jeong, J.-H. (2013), Constrained parametric model for simultaneous inference of two cumulative incidence functions. Biom. J., 55: 82–96. doi: 10.1002/bimj.201200011
- Issue online: 7 JAN 2013
- Version of Record online: 23 OCT 2012
- Manuscript Accepted: 20 AUG 2012
- Manuscript Revised: 15 AUG 2012
- Manuscript Received: 7 JAN 2012
- NSF. Grant Numbers: 0906449, 1207711
- National Health Institute (NIH). Grant Numbers: 5-U10-CA69974-09, 5-U10-CA69651-11
Disclaimer: Supplementary materials have been peer-reviewed but not copyedited.
Table S1 Simulation results on censoring time following a proportional odds model; the data were simulated from the modified logistic or Gompertz base with a proportional subdistribution hazard transformation (LOG+PSH and GOM+PSH) or with a generalized odds-rate transformation (LOG + GOR and GOM + GOR); referring to Table 1 for the definition of AVE, MSE, ESE, and Cov.
Table S2 Simulation results where the data were simulated from our proposed modified logistic (panel LOG + PSH) or Gompertz model (panel GOM + PSH) with complimentary log–log transformation or with generalized odds-rate transformation (panels LOG + GOR and GOM + GOR) with sample size n=500 and 40% censoring rate, where AVE is the average of the estimates, MSE is the average of the model-based standard errors, ESE is the empirical standard error, and Cov is the coverage rates of the 95% Wald confidence intervals.
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