讲座题目：New Perspectives of p-Value and its Strength of Evidence Measured by Confidence Distribution

新视角下的假设检验中的p值——基于置信分布理论的相关研究

主 讲 人：刘斯凡博士（“数字经济与实体经济深度融合研究”科研创新团队）

讲座时间：2021年5月14日 13：30-15：00

讲座地点：N3117

讲座内容：

The notion of p-value is fundamental in statistics. It has been widely used for reporting outcomes of hypothesis tests. However, it is often misinterpreted, misused or miscommunicated. In this article, we first propose a general and rigorous definition of p-value that fulfills two performance-based characteristics of it. The proposal incorporates all existing definitions of the p-value, and justifies their interpretations. The paper further presents a concrete approach to formulate and calculate p-values based on confidence distribution. It has two main advantages. First, it is applicable for a wide range of hypothesis testing problems, including the standard one- and two-sided tests, tests with interval-type null, intersection-union tests, multivariate tests and so on. Second, it can naturally lead to a coherent interpretation of p-value as evidence in support of the null hypothesis, as well as a meaningful measure of degree of such support. Therefore, it places a meaning of a large p-value, e.g., p-value of 0.8 has more support than 0.5. Numerical examples are used to illustrate the wide applicability and computational feasibility of our approach. We show that our proposal is effective and can be applied broadly, without further consideration of the form/size of the null space. As for existing testing methods, the solutions have not been available or cannot be easily obtained.

主讲人简介：

刘斯凡，2018年加入天津财经大学统计学院，2020年加入“数字经济与实体经济深度融合研究”创新团队。本科毕业于北京大学数学系，博士毕业于美国密苏里大学。先后在密苏里州癌症研究所和上海证券交易所中证指数公司从事研究工作。主要研究领域为贝叶斯统计、荟萃分析、假设检验和非参数统计等。在Biostatistics& Epidemiology, Statistics and Its Interface 发表或参与发表与大数据荟萃分析相关的文章两篇, 在Statistical Theory and Related Fields发表假设检验相关的讨论论文一篇。主持华东师范大学统计与数据科学前沿理论及应用教育部重点实验室开放研究课题一项。

刘斯凡博士