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Table 2 Results of simulation studies

From: Augmenting the logrank test in the design of clinical trials in which non-proportional hazards of the treatment effect may be anticipated

Scenario Dataset n Test
    Cox Joint Perm. Comb.
A (null) GOG111 1000 5.2 5.3 4.9 5.3
  PATCH1 1000 5.0 4.9 5.2 4.8
  ICON7 1000 4.8 4.9 5.2 4.9
B (PH) GOG111 652 9 2 . 9 87.2 8 6.7 91.0
  PATCH1 1280 9 2 . 6 8 6.9 87.7 90.2
  ICON7 1240 9 1 . 9 8 6.6 88.3 89.8
C (early) GOG111 310 7 2.5 91.5 9 2 . 1 90.0
  PATCH1 450 7 4.4 88.8 9 1 . 9 89.2
  ICON7 522 3 6.9 9 8 . 7 92.4 89.5
D (late) GOG111 560 92.7 9 6 . 1 8 0.5 90.3
  1. Values in table are percentages of 10,000 (scenario A) or 5,000 (scenarios B–D) simulated datasets in which each of four tests was significant at the 5 percent level. The datasets were simulated to mimic data from three randomized controlled trials with varying sample size (n). Values in bold (or italic) type indicate the most (or least) powerful among the four tests for the given scenario and dataset
  2. Abbreviations: Joint joint test [1], Perm. permutation test, Comb. combined test