Show simple item record

FieldValueLanguage
dc.contributor.authorZhu, Lin
dc.contributor.authorBell, Katy J.L.
dc.contributor.authorScott, Anna Mae
dc.contributor.authorGlasziou, Paul
dc.date.accessioned2023-03-01T03:46:12Z
dc.date.available2023-03-01T03:46:12Z
dc.date.issued2022en_AU
dc.identifier.urihttps://hdl.handle.net/2123/30137
dc.description.abstractRisk prediction models are potentially useful tools for health practitioners and policy makers. When new predictors are proposed to add to existing models, the improvement of discrimination is one of the main measures to assess any increment in performance. In assessing such predictors, we observed two paradoxes: 1) the discriminative ability within all individual risk strata was worse than for the overall population; 2) incremental discrimination after including a new predictor was greater within each individual risk strata than for the whole population. We show two examples of the paradoxes and analyse the possible causes. The key cause of bias is use of the same prediction model as for both stratifying the population, and as the base model to which the new predictor is addeden_AU
dc.language.isoenen_AU
dc.publisherTaylor and Francisen_AU
dc.relation.ispartofF1000Researchen_AU
dc.rightsCreative Commons Attribution 4.0en_AU
dc.subjectROC curveen_AU
dc.subjectC-statisticen_AU
dc.subjectrisk prediction modelsen_AU
dc.subjectheart disease risk factorsen_AU
dc.titleAnalyses within risk strata overestimate gain in discrimination: the example of coronary artery calcium scoresen_AU
dc.typeReport, Researchen_AU
dc.identifier.doi10.12688/f1000research.109490.1
dc.relation.nhmrc1174523
dc.relation.nhmrc1080042
dc.relation.nhmrc2006545
usyd.facultySeS faculties schools::Faculty of Medicine and Health::Sydney School of Public Healthen_AU
workflow.metadata.onlyNoen_AU


Show simple item record

Associated file/s

Associated collections

Show simple item record

There are no previous versions of the item available.