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pro vyhledávání: '"Rava, Denise"'
In this paper we address the challenges posed by non-proportional hazards and informative censoring, offering a path toward more meaningful causal inference conclusions. We start from the marginal structural Cox model, which has been widely used for
Externí odkaz:
http://arxiv.org/abs/2311.07752
We consider a general proportional odds model for survival data under binary treatment, where the functional form of the covariates is left unspecified. We derive the efficient score for the conditional survival odds ratio given the covariates using
Externí odkaz:
http://arxiv.org/abs/2310.14448
Autor:
Rava, Denise, Xu, Ronghui
We consider the conditional treatment effect for competing risks data in observational studies. While it is described as a constant difference between the hazard functions given the covariates, we do not assume specific functional forms for the covar
Externí odkaz:
http://arxiv.org/abs/2112.09535
Autor:
Rava, Denise, Bradic, Jelena
Prognostic models in survival analysis are aimed at understanding the relationship between patients' covariates and the distribution of survival time. Traditionally, semi-parametric models, such as the Cox model, have been assumed. These often rely o
Externí odkaz:
http://arxiv.org/abs/2007.13218
Autor:
Rava, Denise, Xu, Ronghui
We study explained variation under the additive hazards regression model for right-censored data. We consider different approaches for developing such a measure, and focus on one that estimates the proportion of variation in the failure time explaine
Externí odkaz:
http://arxiv.org/abs/2003.09460
Akademický článek
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Autor:
Rava, Denise, Xu, Ronghui
Publikováno v:
Statistics in Medicine; 1/15/2021, Vol. 40 Issue 1, p85-100, 16p
