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@ARTICLE{Lutz:137718,
      author       = {Lutz, Sharon M and Hokanson, John E and Lange, Christoph},
      title        = {{A}n alternative hypothesis testing strategy for secondary
                      phenotype data in case-control genetic association studies.},
      journal      = {Frontiers in genetics},
      volume       = {5},
      issn         = {1664-8021},
      address      = {Lausanne},
      publisher    = {Frontiers Media},
      reportid     = {DZNE-2020-04040},
      pages        = {188},
      year         = {2014},
      abstract     = {Motivated by the challenges associated with accounting for
                      the ascertainment when analyzing secondary phenotypes that
                      are correlated with case-control status, Lin and Zeng have
                      proposed a method that properly reflects the case-control
                      sampling (Lin and Zeng, 2009). The Lin and Zeng method has
                      the advantage of accurately estimating effect sizes for
                      secondary phenotypes that are normally distributed or
                      dichotomous. This method can be computationally intensive in
                      practice under the null hypothesis when the likelihood
                      surface that needs to be maximized can be relatively flat.
                      We propose an extension of the Lin and Zeng method for
                      hypothesis testing that uses proportional odds logistic
                      regression to circumvent these computational issues. Through
                      simulation studies, we compare the power and type-1 error
                      rate of our method to standard approaches and Lin and Zeng's
                      approach.},
      cin          = {U T4 Researchers - Bonn},
      ddc          = {570},
      cid          = {I:(DE-2719)7000008},
      pnm          = {345 - Population Studies and Genetics (POF3-345)},
      pid          = {G:(DE-HGF)POF3-345},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:25071819},
      pmc          = {pmc:PMC4076613},
      doi          = {10.3389/fgene.2014.00188},
      url          = {https://pub.dzne.de/record/137718},
}