Skip to main content

Table 2 Scenarios 25 and 26 – performance measures for estimation of control arm RMST

From: Two-stage estimation to adjust for treatment switching in randomised trials: a simulation study investigating the use of inverse probability weighting instead of re-censoring

Scenario details Method Percent bias Empirical SE of % bias RMSE of % bias Coverage (%) Convergence (%)
Scenario number: 25
True RMST:
Control: 228
Experimental: 269
Mean switch: 25%
True ave. HR: 0.78
True ave. AF: 1.30
Mean censored: 18%
No switching 0.1 5.8 5.8 94.9 100
ITT 2.7 5.8 6.4 92.9 100
TSE 0.3 6.4 6.4 95.6 100
TSEnr 1.0 5.9 6.0 94.8 100
TSEipcw 1.0 6.6 6.7 95.3 100
min/max MC error 0.2/0.2 0.1/0.1 0.1/0.2 0.7/0.8
Scenario number: 26
True RMST:
Control: 228
Experimental: 269
Mean switch: 57%
True ave. HR: 0.78
True ave. AF: 1.30
Mean censored: 18%
No switching 0.0 5.7 5.7 95.6 100
ITT 6.2 5.6 8.4 85.4 100
TSE 0.3 7.1 7.1 95.2 100
TSEnr 1.5 6.4 6.6 95.3 100
TSEipcw 1.8 8.3 8.5 95.2 100
min/max MC error 0.2/0.3 0.1/0.2 0.1/0.3 0.6/1.2
  1. Note: RMST restricted mean survival time, HR hazard ratio, AF acceleration factor, SE standard error, RMSE root mean squared error, MC Monte-Carlo; ITT intention to treat, TSE two-stage estimation, TSEnr two-stage estimation without re-censoring, TSEipcw two-stage estimation with inverse probability of censoring weights