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Research on establishment of decision making method using Bayesian statistics

Research Project

Project/Area Number 19K14587
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 12040:Applied mathematics and statistics-related
Research InstitutionJapanese 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
Project Status Completed (Fiscal Year 2020)
Budget Amount *help
¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2020: ¥130,000 (Direct Cost: ¥100,000、Indirect Cost: ¥30,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Keywordsベイズ統計学 / 生物統計学
Outline of Research at the Start

2016年にアメリカ統計協会から有意確率(以下:P値)に関する声明が発出され、P値の適正な使用と解釈に関する原則が明示された。本声明に対するディスカッションペーパーでは、P値に代わる統計学的方法の1つとしてベイズ統計学の利用が示唆された。これを機にベイズ統計学を用いた意思決定に関するしての議論が活発化している。しかしながら、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。本研究では、ベイズ統計学を用いた意思決定方法の確立(比較の指標とサンプルサイズ設計)を目的とする。

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.

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。

Report

(3 results)
  • 2020 Annual Research Report   Final Research Report ( PDF )
  • 2019 Research-status Report
  • Research Products

    (3 results)

All 2020 2019

All Journal Article (2 results) (of which Peer Reviewed: 2 results,  Open Access: 2 results) Presentation (1 results) (of which Int'l Joint Research: 1 results)

  • [Journal Article] Use of a Smart Watch for Early Detection of Paroxysmal Atrial Fibrillation: Validation Study2020

    • Author(s)
      Tomohiko Inui, Hiroki Kohno, Yohei Kawasaki
    • Journal Title

      JMIR Cardio .

      Volume: 44 Issue: 1 Pages: e14857-e14857

    • DOI

      10.2196/14857

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed / Open Access
  • [Journal Article] Bayesian sample‐size determination methods considering both worthwhileness and unpromisingness for exploratory two‐arm randomized clinical trials with binary endpoints2019

    • Author(s)
      Kakizume Tomoyuki、Zhang Fanghong、Kawasaki Yohei、Daimon Takashi
    • Journal Title

      Pharmaceutical Statistics

      Volume: 19 Issue: 1 Pages: 71-83

    • DOI

      10.1002/pst.1971

    • Related Report
      2020 Annual Research Report 2019 Research-status Report
    • Peer Reviewed / Open Access
  • [Presentation] Comparison of Bayesian equivalency methods for two binomial outcomes using Bayesian index2019

    • Author(s)
      Yohei Kawasaki, Yosuke Inaba, Hanaoka Hanaoka, Etsuo Miyaoka
    • Organizer
      The VIth International Symposium on Biopharmaceutical Statistics
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research

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Published: 2019-04-18   Modified: 2022-01-27  

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