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

被引：5

作者：

Senn, Stephen ^{[1
]}

机构：

[1] Univ Sheffield, Sch Hlth & Related Res, Med Stat Grp, Sheffield, S Yorkshire, England

来源：

PHARMACEUTICAL STATISTICS | 2022年 / 21卷 / 04期

关键词：

Bayesian; conditional inference; design of experiments; frequentist; sequential design; vaccine efficacy; RANDOMIZATION;

D O I：

10.1002/pst.2226

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

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.

引用

页码：790 / 807

页数：18

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