Research on establishment of decision making method using Bayesian statistics

2020 Fiscal Year Final Research Report

• Project/Area Number: 19K14587
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 12040:Applied mathematics and statistics-related
• Research Institution: Japanese Red Cross College of Nursing (2020); Chiba University (2019)
• Principal Investigator: Kawasaki Yohei 日本赤十字看護大学, 看護学部, 准教授 (90711573)
• Project Period (FY): 2019-04-01 – 2021-03-31
• Keywords: ベイズ統計学

Outline of Final Research Achievements

In clinical trials, it is often necessary to perform an equivalence study. The equivalence study requires actively denoting equivalence between two different drugs or treatments. Since it is not possible to assert equivalence that is not rejected by a superiority test, statistical methods known as equivalency tests have been suggested. These methods for equivalency tests are based on the frequency framework; however, there are few such methods in the Bayesian framework. Hence, this paper proposes a new index that suggests the equivalency of binomial proportions, which is constructed based on the Bayesian framework. In this study, we provide two methods for calculating the index and compare the probabilities that have been calculated by these two calculation methods.
Moreover, we apply this index to the results of actual clinical trials to demonstrate the utility of the index.

Free Research Field

統計学

Academic Significance and Societal Importance of the Research Achievements

ベイズ流の解析手法は古くから多くの方法が提案されているが、仮説検定のように「意思決定」につながる方法論は、ベイズ統計学の枠組みでは確立されていないのが現状である。以上のことから、「ベイズ統計学を用いた意思決定の方法」は未だ確立されてはいないという問いに対して、本研究では、ベイズ統計学を用いた意思決定方法の確立を目指すという明確な回答で研究を行う。