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Proportional hazards models with continuous marks
The Annals of Statistics, 2009 For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541--554]. This article studies an extension of
Gilbert, Peter B. +2 more
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Two-Level Proportional Hazards Models [PDF]
Biometrics, 2002 We extend the proportional hazards model to a two-level model with a random intercept term and random coefficients. The parameters in the multilevel model are estimated by a combination of EM and Newton-Raphson algorithms. Even for samples of 50 groups, this method produces estimators of the fixed effects coefficients that are approximately unbiased ...
Maples, Jerry J. +2 more
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Proportional hazards models with discrete frailty [PDF]
Lifetime Data Analysis, 2010 We extend proportional hazards frailty models for lifetime data to allow a negative binomial, Poisson, Geometric or other discrete distribution of the frailty variable. This might represent, for example, the unknown number of flaws in an item under test.
Caroni, Chrys +2 more
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Explained randomness in proportional hazards models [PDF]
Statistics in Medicine, 2005 A coefficient of explained randomness, analogous to explained variation but for non-linear models, was presented by Kent. The construct hinges upon the notion of Kullback-Leibler information gain. Kent and O'Quigley developed these ideas, obtaining simple, multiple and partial coefficients for the situation of proportional hazards regression.
John, O'Quigley +2 more
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DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network [PDF]
BMC Medical Research Methodology, 2016 BackgroundMedical practitioners use survival models to explore and understand the relationships between patients’ covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear
Jared Katzman +5 more
semanticscholar +1 more source
Regularization for Cox's proportional hazards model with NP-dimensionality
, 2012 High throughput genetic sequencing arrays with thousands of measurements per sample and a great amount of related censored clinical data have increased demanding need for better measurement specific model selection.
Bradic, Jelena +2 more
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BMC Musculoskeletal Disorders, 2021 Background Survival analysis and effect of covariates on survival time is a central research interest. Cox proportional hazards regression remains as a gold standard in the survival analysis. The Cox model relies on the assumption of proportional hazards
I. Kuitunen +4 more
semanticscholar +1 more source
Partial Orders with Respect to Continuous Covariates and Tests for the Proportional Hazards Model [PDF]
, 2008 Several omnibus tests of the proportional hazards assumption have been proposed in the literature. In the two-sample case, tests have also been developed against ordered alternatives like monotone hazard ratio and monotone ratio of cumulative hazards ...
Bhattacharjee, Arnab
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A mixed model approach for structured hazard regression [PDF]
, 2004 The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as ...
Fahrmeir, Ludwig, Kneib, Thomas
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An Assessment of the Cox Proportional Hazards Regression Model for Epidemiologic Studies
Risk Analysis, 2018 The basic assumptions of the Cox proportional hazards regression model are rarely questioned. This study addresses whether hazard ratio, i.e., relative risk (RR), estimates using the Cox model are biased when these assumptions are violated.
S. Moolgavkar +3 more
semanticscholar +1 more source