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Breaking barriers in survival analysis: Unlocking the potential of additive hazards models through maximum likelihood
FunderNetherlands Organisation for Scientific Research (NWO)
DurationFrom 01 Sep 2024
Funded underOpen Competitie ENW - M 2022/2023 Pakket 22-6
Project codeOCENW.M.22.408
Open Access mandatePublications: NoResearch data: No
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Description
Breaking barriers in survival analysis: Unlocking the potential of additive hazards models through maximum likelihood The dominant model for time-to-event data is Cox’s proportional hazards model. It is immensely popular because it yields a single effect-measure for the effect of a prognostic factor on the time-to-event through a hazard ratio. When the proportional hazards assumption is invalid, estimates based on the model are severely biased. The additive hazards model is accommodates time-varying effects in a natural way. In this project we develop methodology for additive hazards models based on maximum likelihood, including cross-validation and regularized estimates based on penalized likelihood.
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Breaking barriers in survival analysis: Unlocking the potential of additive hazards models through maximum likelihood The dominant model for time-to-event data is Cox’s proportional hazards model. It is immensely popular because it yields a single effect-measure for the effect of a prognostic factor on the time-to-event through a hazard ratio. When the proportional hazards assumption is invalid, estimates based on the model are severely biased. The additive hazards model is accommodates time-varying effects in a natural way. In this project we develop methodology for additive hazards models based on maximum likelihood, including cross-validation and regularized estimates based on penalized likelihood.
