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Table 3 The empirical powers of the tests at the significance level 0.05 when the survival times have uniform, exponential, log-normal,uniform and exponential, uniform and log-normal, or exponential and log-normal distributions with unequal medians and sample sizes n 1 = 100, n 2 = 150, n 3 = 150, n 4 = 200

From: Comparing survival curves based on medians

Distributions and parameters Censoring rate BC TJ New
Uniform distribution
θ = (10,10,10.5,10)
a = (4,4,4,4)
c = (2,2,2,2)
0 0.602 0.587 0.594
0.1 0.563 0.606 0.549
0.2 0.537 0.622 0.518
0.3 0.509 0.635 0.490
Exponential distribution
θ = (10,10,10,10)
a = (0.1,0.15,0.15,0.1)
0 0.837 0.829 0.833
0.1 0.822 0.831 0.818
0.2 0.799 0.830 0.793
0.3 0.765 0.826 0.756
Log-normal distribution
θ = (10,14,14,10)
a = (1,1,1,1)
0 0.804 0.794 0.797
0.1 0.776 0.800 0.769
0.2 0.729 0.787 0.718
0.3 0.696 0.798 0.681
Two uniform and two exponential distributions
θ = (10,13,13-10log(2),10-10log(2))
a = (0.1,0.1,0.1,0.1)
c = (0.01,0.01,0.01,0.01)
0 0.889 0.883 0.884
0.1 0.838 0.875 0.827
0.2 0.817 0.873 0.801
0.3 0.798 0.874 0.779
Two uniform and two log-normal distributions
θ = (10,12,2.5,2.5)
a = (1,1,1,1)
c = (0.2,0.2,0.2,0.2)
0 0.847 0.821 0.845
0.1 0.751 0.813 0.766
0.2 0.695 0.813 0.706
0.3 0.651 0.815 0.644
Two log-normal and two exponential distributions
θ = (log(10),log(13),13-10log(2),10-10log(2))
a = (1, 1, 0.1, 0.1)
0 0.799 0.790 0.793
0.1 0.761 0.776 0.752
0.2 0.744 0.788 0.727
0.3 0.718 0.795 0.699