| Project/Area Number |
07680317
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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 (1996)
Hokkaido University (1995) |
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Principal Investigator |
SAITO Takayuki Tokyo Institute of Technology, Graduate School of Social Science and Technology, Professor, 大学院・社会理工学研究科, 教授 (70113561)
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| Co-Investigator(Kenkyū-buntansha) |
YUKIHIRO Ryoji Hokkaido University, Department of Behavioral Science, Assistant, 文学部, 助手 (60240628)
齋藤 幸子 工業技術院生命工学工業研究所, 人間情報部, 主任研究官
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| Project Period (FY) |
1995 – 1996
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| Project Status |
Completed (Fiscal Year 1996)
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| Budget Amount *help |
¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 1996: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 1995: ¥800,000 (Direct Cost: ¥800,000)
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| Keywords | redundancy analysis / mixed measurement data / multivariate analysis / educational measurement / sensory evaluation / wearing comfort / offensive odors / 連続変数 / 離散変数 |
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| Research Abstract |
In a variety of disciplines, there is great necesssity to analyze relationships between two sets of multivariates data. Redundancy analysis (RDA), among others, has been proposed to meet such requirement. However there have been few applications of RDA to real data and so its usefulness remained unknown. This research aimed to evaluate RDA through applied studies and also to suggest some development for RDA.
Regading methodological aspect, we suggested an improved procedure (QRDA) of RDA so as to deal with multivariated data at mixed measurement levels, incorporating treatment to deal with degeneracy. We performed three applied studies. First, RDA was applied to educational data in order explore relationships between high school grade point averages and the national center examination tests. Second, RDA was utilized to examine relationships between fabric physical properties of girdles and the wearing comfort. Third, we analyzed sensory inspection data of offensive odors by using QRDA.We clarified relatioships between a set of chemical properties of the odors and another set of psychological variables in terms of sensory evaluation. Through those applications, it was concluded that RDA and QRDA are useful for data analysis.
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