# Table 3 Power (%) to detect a difference of effectiveness between PI-A and PI-B according to the study design and the effectiveness of PI-B (ϵB), assumingϵA= 0.999 and a limit of detection (“ML data”)

ϵ B 0.998 0.995 0.990 0.998 0.995 0.990 0.998 0.995 0.990
Small sample size Design* N = 10 and n = 7 N = 14 and n = 5 N = 10 and n = 5
ntot = 70 ntot = 70 ntot =50
Wald test (uncorrected) 62.2 99.8 100 61.8 100 100 55.2 98.8 100
Wald test (corrected) 44.2 98.4 100 50.4 100 100 35.8 95.8 100
Wilcoxon test 6.6 11.2 26.8 4.4 15.6 39.0 6.6 11.2 26.8
Design* N = 20 and n = 7 N = 28 and n = 5 N = 20 and n = 5
ntot = 140 ntot = 140 ntot = 100
Middle sample size Wald test (uncorrected) 83.4 100 100 86.8 100 100 77.8 100 100
Wald test (corrected) 69.0 100 100 78.0 100 100 58.8 100 100
Wilcoxon test 7.0 23.0 50.4 6.8 30.4 64.6 7.0 23.0 50.4
Large sample size Design* N = 30 and n = 7 N = 42 and n = 5 N = 30 and n = 5
ntot = 210 ntot = 210 ntot = 150
Wald test (uncorrected) 94.0 100 100 86.8 100 100 89.4 100 100
Wald test (corrected) 89.2 100 100 82.6 100 100 82.6 100 100
Wilcoxon test 7.4 31.0 67.0 9.2 43.8 85.0 7.4 31.0 67.0
1. * N: number of patients per group of treatment; n: number of viral load measurements per patient; ntot: total numbers of observations per group of treatment.