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Statistical challenges in assessing and fostering the reproducibility of scientific results [electronic resource] : summary of a workshop

Statistical challenges in assessing and fostering the reproducibility of scientific results [electronic resource] : summary of a workshop

자료유형
E-Book(소장)
개인저자
Schwalbe, Michelle.
단체저자명
National Academies of Sciences, Engineering, and Medicine (U.S.). Committee on Applied and Theoretical Statistics.
서명 / 저자사항
Statistical challenges in assessing and fostering the reproducibility of scientific results [electronic resource] : summary of a workshop / Michelle Schwalbe, rapporteur ; Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Their Applications, Division on Engineering and Physical Sciences, the National Academies of Sciences, Engineering, Medicine.
발행사항
Washington, DC :   The National Academies Press,   c2016.  
형태사항
1 online resource (xii, 120 p.) : ill.
ISBN
9780309392037 (electronic bk.) 0309392039 (electronic bk.) 9780309392020 0309392020
요약
"Questions about the reproducibility of scientific research have been raised in numerous settings and have gained visibility through several high-profile journal and popular press articles. Quantitative issues contributing to reproducibility challenges have been considered (including improper data measurement and analysis, inadequate statistical expertise, and incomplete data, among others), but there is no clear consensus on how best to approach or to minimize these problems. A lack of reproducibility of scientific results has created some distrust in scientific findings among the general public, scientists, funding agencies, and industries. While studies fail for a variety of reasons, many factors contribute to the lack of perfect reproducibility, including insufficient training in experimental design, misaligned incentives for publication and the implications for university tenure, intentional manipulation, poor data management and analysis, and inadequate instances of statistical inference. The workshop summarized in this report was designed not to address the social and experimental challenges but instead to focus on the latter issues of improper data management and analysis, inadequate statistical expertise, incomplete data, and difficulties applying sound statistic inference to the available data. Many efforts have emerged over recent years to draw attention to and improve reproducibility of scientific work. This report uniquely focuses on the statistical perspective of three issues: the extent of reproducibility, the causes of reproducibility failures, and the potential remedies for these failures"--Publisher's description.
일반주기
Title from e-Book title page.  
서지주기
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Research --Statistical methods --Congresses. Research --Methodology --Congresses.
바로가기
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245 0 0 ▼a Statistical challenges in assessing and fostering the reproducibility of scientific results ▼h [electronic resource] : ▼b summary of a workshop / ▼c Michelle Schwalbe, rapporteur ; Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Their Applications, Division on Engineering and Physical Sciences, the National Academies of Sciences, Engineering, Medicine.
260 ▼a Washington, DC : ▼b The National Academies Press, ▼c c2016.
300 ▼a 1 online resource (xii, 120 p.) : ▼b ill.
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
520 1 ▼a "Questions about the reproducibility of scientific research have been raised in numerous settings and have gained visibility through several high-profile journal and popular press articles. Quantitative issues contributing to reproducibility challenges have been considered (including improper data measurement and analysis, inadequate statistical expertise, and incomplete data, among others), but there is no clear consensus on how best to approach or to minimize these problems. A lack of reproducibility of scientific results has created some distrust in scientific findings among the general public, scientists, funding agencies, and industries. While studies fail for a variety of reasons, many factors contribute to the lack of perfect reproducibility, including insufficient training in experimental design, misaligned incentives for publication and the implications for university tenure, intentional manipulation, poor data management and analysis, and inadequate instances of statistical inference. The workshop summarized in this report was designed not to address the social and experimental challenges but instead to focus on the latter issues of improper data management and analysis, inadequate statistical expertise, incomplete data, and difficulties applying sound statistic inference to the available data. Many efforts have emerged over recent years to draw attention to and improve reproducibility of scientific work. This report uniquely focuses on the statistical perspective of three issues: the extent of reproducibility, the causes of reproducibility failures, and the potential remedies for these failures"--Publisher's description.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Research ▼x Statistical methods ▼v Congresses.
650 0 ▼a Research ▼x Methodology ▼v Congresses.
700 1 ▼a Schwalbe, Michelle.
710 2 ▼a National Academies of Sciences, Engineering, and Medicine (U.S.). ▼b Committee on Applied and Theoretical Statistics.
856 4 0 ▼3 EBSCOhost ▼u https://oca.korea.ac.kr/link.n2s?url=http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1204376
945 ▼a KLPA
991 ▼a E-Book(소장)

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 001.422 등록번호 E14012059 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

컨텐츠정보

목차

Section	Section Description	Page Number
1	Introduction	p. 1
    Workshop Overview	p. 2
    Workshop Themes	p. 3
    Organization of this Report	p. 7
2	Overview and Case Studies	p. 8
    Opening Remarks from the Workshop Co-Chairs	p. 9
    Perspectives from Stakeholders	p. 9
    Overview of the Statistical Challenges of Reproducibility	p. 18
    Case Studies	p. 22
3	Conceptualizing, Measuring, and Studying Reproducibility	p. 35
    Definitions and Measures of Reproducibility	p. 36
    Reproducibility and Statistical Significance	p. 48
    Assessment of Factors Affecting Reproducibility	p. 55
    Reproducibility from the Informatics Perspective	p. 61
4	The Way Forward: Using Statistics to Improve Reproducibility	p. 68
    Open Problems, Needs, and Opportunities for Methodologic Research	p. 69
    Reporting Scientific Results and Sharing Scientific Study Data	p. 78
    The Way Forward from the Data Sciences Perspective: Research	p. 89
References	p. 97
Appendixes	
A	    Registered Workshop Participants	p. 109
B	    Workshop Agenda	p. 115
C	    Acronyms	p. 118

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