COVID-19疫苗有效率的置信区间

Q3 Mathematics Numeracy Pub Date : 2021-01-01 DOI:10.5038/1936-4660.14.2.1390
Frank Wang
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引用次数: 0

摘要

本教程使用来自制药商和食品和药物管理局的公开数据,指导学习者使用贝叶斯框架估计COVID-19疫苗有效性的置信区间。在经典方法下,不存在与参数相关的概率,并且没有经验的学生可能会误解置信区间的含义。利用贝叶斯统计,可以找到未知参数的后验概率分布,并陈述疫苗有效率的概率,使得不确定性的沟通更加灵活。我们用一个假设的例子和一个真实的棒球例子来指导读者在分析临床试验数据之前先学习β -二项模型。本笔记是为具有基本统计学和基本代数技能的较低水平的大学生设计的。
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Confidence Intervals of COVID-19 Vaccine Efficacy Rates
This tutorial uses publicly available data from drug makers and the Food and Drug Administration to guide learners to estimate the confidence intervals of COVID-19 vaccine efficacy rates with a Bayesian framework. Under the classical approach, there is no probability associated with a parameter, and the meaning of confidence intervals can be misconstrued by inexperienced students. With Bayesian statistics, one can find the posterior probability distribution of an unknown parameter, and state the probability of vaccine efficacy rate, which makes the communication of uncertainty more flexible. We use a hypothetical example and a real baseball example to guide readers to learn the beta-binomial model before analyzing the clinical trial data. This note is designed to be accessible for lower-level college students with elementary statistics and elementary algebra skills.
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来源期刊
Numeracy
Numeracy Mathematics-Mathematics (miscellaneous)
CiteScore
1.30
自引率
0.00%
发文量
13
审稿时长
12 weeks
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