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UID:20251121T113431EST-9779x8pIGU@132.216.98.100
DTSTAMP:20251121T163431Z
DESCRIPTION:New tests to check the main assumptions of a flexible parametri
 c excess hazard model.\n\n\n	In many clinical prognostic studies of patient
 s diagnosed with a particular disease\, individual causes of death remain 
 unknown. Net survival\, the one that would be observed if the disease unde
 r study were the only cause of death\, is an important and increasingly us
 ed indicator in public health\, especially in population-based studies. Es
 timates of net survival and of the effects of prognostic factors on net su
 rvival\, can be obtained by excess hazard regression modeling. However\, w
 hereas various diagnostic tools were developed for overall survival analys
 is\, few methods are available to check the assumptions of excess hazard m
 odels. We propose two formal tests to check the proportional hazards assum
 ption and the validity of the functional forms of the covariate effects in
  the context of flexible parametric excess hazard modeling. These tests we
 re adapted from martingale-residual-based tests for parametric modeling of
  overall survival to allow adding to the model a necessary element for net
  survival analysis: the population mortality hazard. We studied the size a
 nd the power of these tests through an extensive simulation study based on
  complex but realistic data. The new tests showed sizes close to the nomin
 al values and satisfactory powers. The power of the proportionality test w
 as similar or greater than that of other tests already available in the fi
 eld of net survival. We illustrate the use of these tests with real data f
 rom French cancer registries.\n
DTSTART:20170314T193000Z
DTEND:20170314T203000Z
LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Coraline Danieli\, PhD\, Postdoctoral Fellow - ɬÀï·¬
URL:/mathstat/channels/event/coraline-danieli-phd-post
 doctoral-fellow-mcgill-university-266905
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