2001 Fiscal Year Final Research Report Summary
Statistical Models for Causal Inference
| Project/Area Number |
12680312
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
MIYAKAWA Masami Tokyo Institute of Technology, Graduate School of Decision Science and Technology, Professor, 大学院・社会理工学研究科, 教授 (90157595)
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| Co-Investigator(Kenkyū-buntansha) |
NAGATA Yasushi Waseda University, Department of Science and Engineering, Professor, 理工学部, 教授 (30198337)
SATO Toshiya Kyoto University, School of Public Health, Professor, 大学院・医学研究科, 教授 (50187217)
EGUCHI Shinto Institute of Statistical Mathmatics, Tokyo Institute of Technology, Professor, 基礎研究系, 教授 (10168776)
NISHINA Ken Nagoya Institute of Technology, Department of Engineering, Associate Professor, 工学部, 助教授 (60115681)
NAKANISHI Hiroko Seikei University , Department of Economics, Professor, 経済学部, 教授 (60207834)
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| Project Period (FY) |
2000 – 2001
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| Keywords | Potential response model / Instrumental variables / Structural equation model / Graphical model |
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| Research Abstract |
In this research, statistical inference procedures of causal diagram using graphical modeling and covariance structure analysis are discussed. We formulate the causal interpretation and outline the proper use of structural equation model and potential response model. The randomization-based estimator of causal effect is given which is interpreted as an extension of the instrumental variables estimator. The inference problem of joint interventions in some treatment variables is also investigated. The parametric expressions for the joint intervention effects using the linear structural equation model are given.
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