| Project/Area Number |
16K16017
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Statistical science
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| Research Institution | Hiroshima University (2019)
Kanazawa University (2016-2018) |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 正確な推測 / 並び替え法 / 因果効果 / モデル化 / 生物統計学 / 臨床試験 |
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| Outline of Final Research Achievements |
The purpose of this study was to develop a new inferential method for the evaluation of effect of a series of treatments or a treatment in the setting of sequential intervention in clinical studies. Existing estimation methods require strong assumptions based on a statistical model in general, but a newly proposed estimator are not subject to such restrictions. The simulation study was performed under a typical setting in clinical studies, and it was robust against the assumption of the statistical model, which was the limit of the conventional method.
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| Academic Significance and Societal Importance of the Research Achievements |
2つ以上の治療法を組み合わせ、かつ逐次的に実施する治療法を逐次治療と言う。特に致死的な疾患においては、1つの治療法のみでは期待するような治療効果を得ることは稀であり、適切な逐次治療を開発することの意義は大きい。一方で、統計的に逐次治療の効果を評価する上では、従来の方法では統計モデル上に強い仮定が必要となるため、仮定が正しくない場合には適切な結論を導くのは困難であった。本研究では、この問題を解決する評価手法について、新たな方法を開発することができた。
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