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Table 2 Type I error, power and coverage probability by sample size and number of trials

From: Characteristics of a loop of evidence that affect detection and estimation of inconsistency: a simulation study

  Balanced scenario(KAB= KAC= KBC= K) Imbalanced scenario
  K = 1 K = 2 K = 3 K = 4 K = 5 K = 6 K = 7 KAB=1
KAC=4
         KBC=7
Type I error (IF = 0)
n ~ U(20,50) 0.07 0.07 0.06 0.04 0.05 0.05 0.04 0.06
n ~ U(50,150) 0.10 0.07 0.06 0.06 0.05 0.06 0.04 0.08
n ~ U(150,300) 0.13 0.07 0.05 0.06 0.06 0.04 0.05 0.06
Power (IF = 0.6)
n ~ U(20,50) 0.13 0.15 0.18 0.23 0.27 0.33 0.37 0.16
n ~ U(50,150) 0.25 0.30 0.42 0.52 0.62 0.70 0.76 0.32
n ~ U(150,300) 0.42 0.54 0.70 0.79 0.84 0.88 0.89 0.49
Coverage Probability (IF = 0.6)
n ~ U(20,50) 0.96 0.96 0.97 0.98 0.97 0.97 0.97 0.97
n ~ U(50,150) 0.95 0.96 0.97 0.96 0.96 0.96 0.96 0.95
n ~ U(150,300) 0.93 0.95 0.94 0.94 0.96 0.95 0.95 0.95
  1. Results are presented for frequent events and aggregated over different assumptions for heterogeneity and methods to estimate the variances of the mean treatment effects. In bold we present results from loops in which the total number of individuals is between 2400 and 3000. n: sample size, K: number of trials.