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@ARTICLE{Kuss:180200,
      author       = {O. Kuss and H. Becher and A. Wienke and T. Ittermann and S.
                      Ostrzinski and S. Schipf and C. O. Schmidt and M. Leitzmann
                      and T. Pischon and L. Krist and S. Roll and M. Sand and H.
                      Pohlabeln and S. Rach and K.-H. Jöckel and A. Stang and U.
                      A. Mueller and A. Werdecker and R. Westerman and K. H.
                      Greiser$^*$ and K. B. Michels},
      title        = {{S}tatistical {A}nalysis in the {G}erman {N}ational
                      {C}ohort ({NAKO}) - {S}pecific {A}spects and {G}eneral
                      {R}ecommendations.},
      journal      = {European journal of epidemiology},
      volume       = {37},
      number       = {4},
      issn         = {0393-2990},
      address      = {Dordrecht [u.a.]},
      publisher    = {Springer Science + Business Media B.V.},
      reportid     = {DKFZ-2022-01169},
      pages        = {429-436},
      year         = {2022},
      note         = {2022 Apr;37(4):429-436},
      abstract     = {The German National Cohort (NAKO) is an ongoing,
                      prospective multicenter cohort study, which started
                      recruitment in 2014 and includes more than 205,000 women and
                      men aged 19-74 years. The study data will be available to
                      the global research community for analyses. Although the
                      ultimate decision about the analytic methods will be made by
                      the respective investigator, in this paper we provide the
                      basis for a harmonized approach to the statistical analyses
                      in the NAKO. We discuss specific aspects of the study (e.g.,
                      data collection, weighting to account for the sampling
                      design), but also give general recommendations which may
                      apply to other large cohort studies as well.},
      keywords     = {Biostatistics (Other) / Cohort Studies (Other) / Data
                      interpretation, statistical (Other) / Follow-Up studies
                      (Other) / Prospective studies (Other)},
      cin          = {C020},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:35653006},
      doi          = {10.1007/s10654-022-00880-7},
      url          = {https://inrepo02.dkfz.de/record/180200},
}