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Statistics in Medicine, 2021 The Cox proportional hazards model is used extensively in clinical and epidemiological research. A key assumption of this model is that of proportional hazards.
P. Austin, Jiming Fang, Douglas S. Lee
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Comparison of regression imputation methods of baseline covariates that predict survival outcomes
Journal of Clinical and Translational Science, 2021 Introduction: Missing data are inevitable in medical research and appropriate handling of missing data is critical for statistical estimation and making inferences.
Nicole Solomon +2 more
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Proportional hazards models with continuous marks [PDF]
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 this approach to allow a continuum of competing risks, in which the cause of failure is replaced by
Sun, Yanqing +2 more
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A Dynamic Semiparametric Proportional Hazard Model [PDF]
SSRN Electronic Journal, 2006 In this paper, we model the buy and sell arrival process in the limit order book market at the Australian Stock Exchange. Using a bivariate autoregressive intensity model we analyze the contemporaneous buy and sell intensity as a function of the state of the market.
Nikolaus Hautsch +2 more
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Adjusting for bias introduced by instrumental variable estimation in the Cox proportional hazards model. [PDF]
Biostatistics, 2017 Instrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably the two-stage residual inclusion (2SRI) algorithm ...
P. Martínez-Camblor +4 more
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Testing proportional hazards for specified covariates
Modern Stochastics: Theory and Applications, 2019 Tests for proportional hazards assumption concerning specified covariates or groups of covariates are proposed. The class of alternatives is wide: log-hazard rates under different values of covariates may cross, approach, go away.
Vilijandas Bagdonavičius +1 more
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BMC Research Notes, 2017 Background Uganda just like any other Sub-Saharan African country, has a high under-five child mortality rate. To inform policy on intervention strategies, sound statistical methods are required to critically identify factors strongly associated with ...
Justine B. Nasejje, Henry Mwambi
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Bayesian Analysis of Masked Competing Risks Data Based on Proportional Subdistribution Hazards Model
Mathematics, 2022 Masked issues can emerge when dealing with competing risk data. Such issues are exemplified by the cause of a particular failure not being directly exhibited for all units to observe but only proven to be a subset of possible causes of failure.
Yosra Yousif +3 more
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Regression Models for Lifetime Data: An Overview
Stats, 2022 Two methods dominate the regression analysis of time-to-event data: the accelerated failure time model and the proportional hazards model. Broadly speaking, these predominate in reliability modelling and biomedical applications, respectively.
Chrys Caroni
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Frontiers in Applied Mathematics and Statistics, 2023 Numerous methods and approaches have been developed for generating time-to-event data from the Cox Proportional Hazards (CPH) model; however, they often require specification of a parametric distribution for the baseline hazard even though the CPH model ...
Jennifer L. Delzeit, Devin C. Koestler
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