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Table 1 Scenarios 20 and 28 – 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: 20

True RMST:

Control: 357

Experimental: 430

Mean switch: 57%

True ave. HR: 0.57

True ave. AF: 1.53

Mean censored: 50%

No switching

0.0

3.7

3.7

94.4

100.0

ITT

7.5

3.4

8.3

46.7

100.0

TSE

−2.3

6.9

7.3

97.8

100.0

TSEnr

3.5

3.9

5.3

86.1

100.0

TSEipcw

−5.1

16.3

17.1

96.0

95.8

min/max MC error

0.1/0.5

0.1/0.4

0.1/0.5

0.5/1.6

–

Scenario number: 28

True RMST:

Control: 228

Experimental: 322

Mean switch: 57%

True ave. HR: 0.56

True ave. AF: 1.85

Mean censored: 26%

No switching

−0.1

5.7

5.7

94.7

100.0

ITT

15.1

5.5

16.0

29.1

100.0

TSE

−3.5

9.1

9.8

93.0

100.0

TSEnr

4.0

6.5

7.6

91.6

100.0

TSEipcw

1.1

11.3

11.3

97.1

99.9

min/max MC error

0.2/0.4

0.1/0.3

0.1/0.8

0.5/1.4

–

  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