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Ten Simple Rules for Reducing Overoptimistic Reporting in Methodological Computational Research

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  • Anne-Laure Boulesteix

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  • Anne-Laure Boulesteix, 2015. "Ten Simple Rules for Reducing Overoptimistic Reporting in Methodological Computational Research," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-6, April.
    • Handle: RePEc:plo:pcbi00:1004191
    DOI: 10.1371/journal.pcbi.1004191
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    References listed on IDEAS

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    1. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    2. Philip E Bourne, 2005. "Ten Simple Rules for Getting Published," PLOS Computational Biology, Public Library of Science, vol. 1(5), pages 1-2, October.
    3. Harriet Dashnow & Andrew Lonsdale & Philip E Bourne, 2014. "Ten Simple Rules for Writing a PLOS Ten Simple Rules Article," PLOS Computational Biology, Public Library of Science, vol. 10(10), pages 1-5, October.
    4. Anne-Laure Boulesteix & Robert Hable & Sabine Lauer & Manuel J. A. Eugster, 2015. "A Statistical Framework for Hypothesis Testing in Real Data Comparison Studies," The American Statistician, Taylor & Francis Journals, vol. 69(3), pages 201-212, August.
    5. John P A Ioannidis, 2014. "How to Make More Published Research True," PLOS Medicine, Public Library of Science, vol. 11(10), pages 1-6, October.
    6. Weixiong Zhang, 2014. "Ten Simple Rules for Writing Research Papers," PLOS Computational Biology, Public Library of Science, vol. 10(1), pages 1-3, January.
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    Cited by:

    1. Christian Hennig, 2022. "An empirical comparison and characterisation of nine popular clustering methods," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(1), pages 201-229, March.
    2. Silke Janitza & Ender Celik & Anne-Laure Boulesteix, 2018. "A computationally fast variable importance test for random forests for high-dimensional data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(4), pages 885-915, December.
    3. Theresa Ullmann & Anna Beer & Maximilian Hünemörder & Thomas Seidl & Anne-Laure Boulesteix, 2023. "Over-optimistic evaluation and reporting of novel cluster algorithms: an illustrative study," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(1), pages 211-238, March.

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