The design and analysis of vaccine trials for COVID-19 for the purpose of estimating efficacy

Stephen Senn*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)

Abstract

After a preliminary explanation as to how I came to know Andy Grieve and some remarks about his career and mine and how they have intersected, I consider the design and analysis of trials of vaccines for COVID-19 for the purpose of estimating efficacy. Five large trials, run by the sponsors Pfizer/BioNTech, AstraZeneca/Oxford University, Moderna, Novavax and J&J Janssen are considered briefly. Frequentist approaches to analysis were used for four of the trials but Pfizer/BioNTech nominated a Bayesian approach. The design and analysis of this trial is considered in some detail, in particular as regards the choice of prior distribution. I conclude by drawing some general lessons.

Original languageEnglish
Pages (from-to)790-807
Number of pages18
JournalPharmaceutical Statistics
Volume21
Issue number4
DOIs
Publication statusPublished - 1 Jul 2022
Externally publishedYes

Keywords

  • Bayesian
  • conditional inference
  • design of experiments
  • frequentist
  • sequential design
  • vaccine efficacy

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