Selected article for: "baseline value and box plot lower end"
Author: Qingyang Xu; Shomesh Chaudhuri; Danying Xiao; Andrew W Lo
Title: Bayesian Adaptive Clinical Trials for Anti-Infective Therapeutics during Epidemic Outbreaks
  • Document date: 2020_4_14
    • ID: 20hk99h4_91
    Snippet: Page 20 of 27 All Rights Reserved Figure 5 . Sensitivity of optimal sample size (in each arm of non-adaptive Bayesian RCT) to the signal to noise ratio (SNR) of treatment effect . From the upper to lower end of each box plot, the five-parameter summary corresponds to [50%, 75%, 100%, 125%, 150%] of the baseline value . used in our analysis (Table 1 ). Figure 6 . Sensitivity of optimal Type I error rate to the signal to noise ratio (SNR) of treatm.....
    Document: Page 20 of 27 All Rights Reserved Figure 5 . Sensitivity of optimal sample size (in each arm of non-adaptive Bayesian RCT) to the signal to noise ratio (SNR) of treatment effect . From the upper to lower end of each box plot, the five-parameter summary corresponds to [50%, 75%, 100%, 125%, 150%] of the baseline value . used in our analysis (Table 1 ). Figure 6 . Sensitivity of optimal Type I error rate to the signal to noise ratio (SNR) of treatment effect . From the upper to lower end of each box plot, the five-parameter summary corresponds to [50%, 75%, 100%, 125%, 150%] of the baseline value . used in our analysis (Table 1) .

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