Table 1.

Independent competing risks: comparison of competing risks regression models under different scenarios

Model estimates (group B/A ratio)
Specified hazardsCoxFine–Gray
ScenarioGroup AGroup BCHR (95% CI)SHR (95% CI)
Scenario I: No difference for either event
 Event 1λ11 = 1.00λ21 = 1.000.993 (0.731–1.349)0.994 (0.737–1.343)
 Event 2λ12 = 1.00λ22 = 1.001.000 (0.736–1.359)1.003 (0.743–1.355)
Scenario II: Event 1 rate lower in group A
 Event 1λ11 = 0.50λ21 = 1.002.013 (1.428–2.839)1.794 (1.286–2.503)
 Event 2λ12 = 1.00λ22 = 1.000.999 (0.750–1.331)0.750 (0.567–0.991)
Scenario III: Both event rates lower in group A
 Event 1λ11 = 0.50λ21 = 1.002.002 (1.451–2.763)1.291 (0.956–1.742)
 Event 2λ12 = 0.50λ22 = 1.002.003 (1.452–2.762)1.292 (0.958–1.744)
Scenario IV: Large and small effects in group A
 Event 1λ11 = 0.50λ21 = 1.002.002 (1.441–2.802)1.555 (1.133–2.135)
 Event 2λ12 = 0.75λ22 = 1.001.333 (0.988–1.799)0.939 (0.704–1.251)

NOTE: Competing risks data were simulated from a bivariate exponential failure distribution with the hazard parameters indicated and independent censoring that resulted in about 33% of lifetimes being censored. Averages of estimated parameters are based on 3,000 simulated data sets, each with sample size N = 250.