Development of new statistical models in categorical data analysis
| Project/Area Number |
26730017
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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 | Osaka City University (2016)
Osaka University (2014-2015) |
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Principal Investigator |
Yamamoto Kouji 大阪市立大学, 大学院医学研究科, 特命准教授 (10548176)
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| Co-Investigator(Renkei-kenkyūsha) |
TOMIZAWA Sadao 東京理科大学, 理工学部, 教授 (50188778)
SHINTANI Ayumi 大阪市立大学, 大学院・医学研究科, 教授 (00724395)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2014: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
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| Keywords | 分割表解析 / 診断研究 / 正確検定 / 順序カテゴリ / 経時データ / 統計モデル / モデルの分解 / 累積確率モデル / 直交分解 / カテゴリ併合 |
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| Outline of Final Research Achievements |
Categorical data, which have some categories like "Response", "Stable" and "Progression" in evaluating a treatment, have been analyzed by using statistical models. Such data are summarized into "contingency tables".
In this research, I have proposed some new statistical models so that we can analyze such contingency table data in more detail.
These development is meaningful in not only mathematical aspect but application one.
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Report
(4 results)
Research Products
(14 results)
