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@ARTICLE{Hofner:128798,
      author       = {B. Hofner and M. Schmid and L. Edler$^*$},
      title        = {{R}eproducible research in statistics: {A} review and
                      guidelines for the {B}iometrical {J}ournal.},
      journal      = {Biometrical journal},
      volume       = {58},
      number       = {2},
      issn         = {0323-3847},
      address      = {Berlin},
      publisher    = {Wiley-VCH},
      reportid     = {DKFZ-2017-04811},
      pages        = {416 - 427},
      year         = {2016},
      abstract     = {Reproducible research (RR) constitutes the idea that a
                      publication should be accompanied by all relevant material
                      to reproduce the results and findings of a scientific work.
                      Hence, results can be verified and researchers are able to
                      build upon these. Efforts of the Biometrical Journal over
                      the last five years have increased the number of manuscripts
                      which are reproducible by a factor of 4 to almost $50\%.$
                      Yet, more than half of the code submission could not be
                      executed in the initial review due to missing code, missing
                      data or errors in the code. Careful checks of the submitted
                      code as part of the reviewing process are essential to
                      eliminate these issues and to foster RR. In this article, we
                      reviewed n=56 recent submissions of code and data to
                      identify common reproducibility issues. Based on these
                      findings, guidelines for structuring code submission to the
                      Biometrical Journal have been established to help authors.
                      These guidelines should help researchers to implement RR in
                      general. Together with the code reviews, this supports the
                      mission of the Biometrical Journal in publishing highest
                      quality, novel and relevant papers on statistical methods
                      and their applications in life sciences. Source code and
                      data to reproduce the presented data analyses are available
                      as Supplementary Material on the journal's web page.},
      cin          = {C060},
      ddc          = {570},
      cid          = {I:(DE-He78)C060-20160331},
      pnm          = {313 - Cancer risk factors and prevention (POF3-313)},
      pid          = {G:(DE-HGF)POF3-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:26711717},
      doi          = {10.1002/bimj.201500156},
      url          = {https://inrepo02.dkfz.de/record/128798},
}