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2016 Fiscal Year Final Research Report

Development of statistical method for case-cohort design when measurements of interests are known to be missing

Research Project

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Project/Area Number 25330039
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Statistical science
Research InstitutionShiga University (2016)
Oita University (2013-2015)

Principal Investigator

Izumi Shizue (大久保志津恵)  滋賀大学, データサイエンス教育研究センター, 教授 (70344413)

Co-Investigator(Renkei-kenkyūsha) TAKEUCHI AYANO  慶應義塾大学, 医学部, 専任講師 (80511196)
Cologne John  放射線影響研究所, 統計部, 研究員 (50344411)
Research Collaborator SUENAGA SATOSHI  
NAGATA DAIKI  
Project Period (FY) 2013-04-01 – 2017-03-31
Keywords医薬生物 / ゲノム統計解析 / ビッグデータ活用 / ゲノム疫学
Outline of Final Research Achievements

In the case-cohort study, costly and laborious research can be greatly saved by measuring expensive genome information only from selected subjects, not the entire cohort. However, since data observed from the target frequently includes missing values, data analysis becomes difficult. In this study, we developed a novel theoretical framework for case-cohort studies when measurements of interests are known to be missing. We also examined the application of the proposed method to large-scale genomic epidemiological studies. From results verified by numerical experiments, when the outcomes of the majority of the subjects in the cohort are missing, the sub-cohort extraction or data analysis performed by the traditional method leads bias in the effects of the interesting variable.

Free Research Field

総合領域

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Published: 2018-03-22  

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