Literature DB >> 25670866

Opinion: Reproducible research can still be wrong: adopting a prevention approach.

Jeffrey T Leek1, Roger D Peng2.   

Abstract

Mesh：

Year:  2015        PMID： 25670866      PMCID： PMC4330755          DOI： 10.1073/pnas.1421412111

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN： 0027-8424            Impact factor:   11.205


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  4 in total

1.  An estimate of the science-wise false discovery rate and application to the top medical literature.

Authors:  Leah R Jager; Jeffrey T Leek
Journal:  Biostatistics       Date:  2013-09-25       Impact factor: 5.899

2.  Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences.

Authors:  Jeremy Goecks; Anton Nekrutenko; James Taylor
Journal:  Genome Biol       Date:  2010-08-25       Impact factor: 13.583

3.  A randomized trial in a massive online open course shows people don't know what a statistically significant relationship looks like, but they can learn.

Authors:  Aaron Fisher; G Brooke Anderson; Roger Peng; Jeff Leek
Journal:  PeerJ       Date:  2014-10-16       Impact factor: 2.984

4.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613
  4 in total
  26 in total

1.  Statistics: P values are just the tip of the iceberg.

Authors:  Jeffrey T Leek; Roger D Peng
Journal:  Nature       Date:  2015-04-30       Impact factor: 49.962

2.  An integrated platform for intuitive mathematical programming modeling using LaTeX.

Authors:  Charalampos P Triantafyllidis; Lazaros G Papageorgiou
Journal:  PeerJ Comput Sci       Date:  2018-09-10

3.  A database of human exposomes and phenomes from the US National Health and Nutrition Examination Survey.

Authors:  Chirag J Patel; Nam Pho; Michael McDuffie; Jeremy Easton-Marks; Cartik Kothari; Isaac S Kohane; Paul Avillach
Journal:  Sci Data       Date:  2016-10-25       Impact factor: 6.444

4.  Removing inter-subject technical variability in magnetic resonance imaging studies.

Authors:  Jean-Philippe Fortin; Elizabeth M Sweeney; John Muschelli; Ciprian M Crainiceanu; Russell T Shinohara
Journal:  Neuroimage       Date:  2016-02-23       Impact factor: 6.556

5.  Cautionary Note on Using Cross-Validation for Molecular Classification.

Authors:  Li-Xuan Qin; Huei-Chung Huang; Colin B Begg
Journal:  J Clin Oncol       Date:  2016-11-10       Impact factor: 44.544

6.  Harmonization of multi-site diffusion tensor imaging data.

Authors:  Jean-Philippe Fortin; Drew Parker; Birkan Tunç; Takanori Watanabe; Mark A Elliott; Kosha Ruparel; David R Roalf; Theodore D Satterthwaite; Ruben C Gur; Raquel E Gur; Robert T Schultz; Ragini Verma; Russell T Shinohara
Journal:  Neuroimage       Date:  2017-08-18       Impact factor: 6.556

7.  Opinion: Reproducibility failures are essential to scientific inquiry.

Authors:  A David Redish; Erich Kummerfeld; Rebecca Lea Morris; Alan C Love
Journal:  Proc Natl Acad Sci U S A       Date:  2018-05-15       Impact factor: 11.205

8.  Comment: Addressing the Need for Portability in Big Data Model Building and Calibration.

Authors:  Chirag J Patel; Francesca Dominici
Journal:  J Am Stat Assoc       Date:  2016-05-05       Impact factor: 5.033

9.  CoINcIDE: A framework for discovery of patient subtypes across multiple datasets.

Authors:  Catherine R Planey; Olivier Gevaert
Journal:  Genome Med       Date:  2016-03-09       Impact factor: 11.117

10.  Improving the reproducibility of findings by updating research methodology.

Authors:  Joseph Klein
Journal:  Qual Quant       Date:  2021-07-08
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