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. 2013 Apr 25;13:60. doi: 10.1186/1471-2288-13-60

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), assuming ϵA = 0.999 and a limit of detection (“ML data”)

  ϵB 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

* 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.