Selected article for: "bayesian RCT model and sample size"
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_53
    Snippet: We repeat the above analysis for RCT of vaccines using a prior probability of having an effective vaccine 40% as reported at https://projectalpha.mit.edu for 2019Q4. The simulation results are summarized in Table 4 . Overall, we observe the same pattern in the optimal sample size and Type I error rates on infectivity, mortality, and proportion of initial infections. However, since is higher for vaccines, the Bayesian decision model requires fewer.....
    Document: We repeat the above analysis for RCT of vaccines using a prior probability of having an effective vaccine 40% as reported at https://projectalpha.mit.edu for 2019Q4. The simulation results are summarized in Table 4 . Overall, we observe the same pattern in the optimal sample size and Type I error rates on infectivity, mortality, and proportion of initial infections. However, since is higher for vaccines, the Bayesian decision model requires fewer subjects on average in the RCT to ascertain the positive effects of the vaccine, compared to the case of anti-infective therapeutics in Table 3 . We find that vaccines should receive even more expedited evaluation.

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