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Table 5 Empirical power according to scenarios in setting 2 (non-exponential case) using both measures (gAHR/nHR)

From: Using the geometric average hazard ratio in sample size calculation for time-to-event data with composite endpoints

  

Power descriptive

 

s

Min

Q1

Med

Q3

Max

Treatment effect

      

Any HRj=0.6

1800/1800

0.782/0.208

0.794/0.596

0.797/0.770

0.801/0.884

0.813/0.997

HR1=HR2=0.9

288/336

0.789/0.724

0.797/0.762

0.800/0.774

0.803/0.786

0.810/0.804

Other cases

1080/1080

0.787/0.457

0.796/0.692

0.799/0.772

0.802/0.835

0.812/0.957

Observed proportions

      

Any \(p_{j}^{(0)}=0.05\)

1440/1488

0.782/0.208

0.794/0.645

0.797/0.777

0.801/0.870

0.813/0.997

\(p_{1}^{(0)}=p_{2}^{(0)} \ge 0.3\)

648/648

0.788/0.420

0.797/0.717

0.800/0.768

0.802/0.790

0.813/0.949

Other cases

1080/1080

0.783/0.250

0.796/0.609

0.798/0.766

0.801/0.878

0.811/0.991

Correlation

      

Weak (ρ=0.1)

1056/1072

0.783/0.252

0.795/0.693

0.799/0.789

0.801/0.859

0.811/0.995

Mild (ρ=0.3)

1056/1072

0.783/0.226

0.795/0.671

0.798/0.770

0.801/0.841

0.813/0.996

Moderate (ρ=0.5)

1056/1072

0.782/0.208

0.795/0.645

0.798/0.753

0.801/0.828

0.812/0.997

Laws of the components

      

β1=β2=0.5

396/402

0.786/0.223

0.796/0.676

0.798/0.771

0.801/0.844

0.812/0.995

β1=β2=2

396/402

0.783/0.219

0.796/0.680

0.799/0.770

0.801/0.842

0.811/0.995

β1β2

2376/2412

0.782/0.208

0.795/0.677

0.798/0.772

0.801/0.840

0.813/0.997

Global

3168/3216

0.782/0.208

0.795/0.677

0.798/0.771

0.801/0.841

0.813/0.997

  1. First column (s) is the number of scenarios. Min: minimum; Q1: first quartile; Med: Median; Q3: third quartile; Max: maximum