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@ARTICLE{Edelmann:156917,
      author       = {D. Edelmann$^*$ and M. Saadati$^*$ and H. Putter and J.
                      Goeman},
      title        = {{A} global test for competing risks survival analysis.},
      journal      = {Statistical methods in medical research},
      volume       = {29},
      number       = {12},
      issn         = {1477-0334},
      address      = {London [u.a.]},
      publisher    = {Sage},
      reportid     = {DKFZ-2020-01224},
      pages        = {3666-3683},
      year         = {2020},
      note         = {2020 Dec;29(12):3666-3683#EA:C060#},
      abstract     = {Standard tests for the Cox model, such as the likelihood
                      ratio test or the Wald test, do not perform well in
                      situations, where the number of covariates is substantially
                      higher than the number of observed events. This issue is
                      perpetuated in competing risks settings, where the number of
                      observed occurrences for each event type is usually rather
                      small. Yet, appropriate testing methodology for competing
                      risks survival analysis with few events per variable is
                      missing. In this article, we show how to extend the global
                      test for survival by Goeman et al. to competing risks and
                      multistate models[Per journal style, abstracts should not
                      have reference citations. Therefore, can you kindly delete
                      this reference citation.]. Conducting detailed simulation
                      studies, we show that both for type I error control and for
                      power, the novel test outperforms the likelihood ratio test
                      and the Wald test based on the cause-specific hazards model
                      in settings where the number of events is small compared to
                      the number of covariates. The benefit of the global tests
                      for competing risks survival analysis and multistate models
                      is further demonstrated in real data examples of cancer
                      patients from the European Society for Blood and Marrow
                      Transplantation.},
      cin          = {C060},
      ddc          = {610},
      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:32631137},
      doi          = {10.1177/0962280220938402},
      url          = {https://inrepo02.dkfz.de/record/156917},
}