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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