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Regression analysis of bivariate current status data under the proportional hazards model
, 2017This article discusses the regression analysis of bivariate current status or case I interval‐censored failure time data under the marginal proportional hazards model.
T. Hu, Qingning Zhou, Jianguo Sun
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Mixtures of proportional hazards regression models
Statistics in Medicine, 1999This paper presents a mixture model which combines features of the usual Cox proportional hazards model with those of a class of models, known as mixtures-of-experts. The resulting model is more flexible than the usual Cox model in the sense that the log hazard ratio is allowed to vary non-linearly as a function of the covariates.
Ori Rosen +2 more
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Proportional Hazards Models of Graduation
Journal of College Student Retention: Research, Theory & Practice, 2007Survival analysis is a statistical tool used to describe the duration between events. Many processes in medical research, engineering, and economics can be described using survival analysis techniques. This research involves studying engineering college student graduation using Cox proportional hazards models. Among male students with American College
Justin R. Chimka +2 more
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Proportional hazards model: a review [PDF]
Reliability Engineering & System Safety, 1994 Abstract The proportional hazards model was introduced in 1972 by D. R. Cox in order to estimate the effects of different covariates influencing the times to the failures of a system. The model has been used rather extensively in biomedicine and, recently, interest in its application in reliability engineering has increased.
Dhananjay Kumar, Bengt Klefsjö
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Proportional hazards models in epidemiology
2021The basic questions of epidemiology are reconsidered in this chapter from the standpoint of a survival model. We rework the calculations of relative risk, where the time factor is now age, and we see how our survival models can be used to control for the effects of age.
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Model misspecification in proportional hazards regression
Biometrika, 1995The proportional hazards model is frequently used to evaluate the effect of treatment on failure time events in randomised clinical trials. Concomitant variables are usually available and may be considered for use in the primary analyses under the assumption that incorporating them may reduce bias or improve efficiency.
Garnet L. Anderson, Thomas R. Fleming
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The consequences of proportional hazards based model selection
Statistics in Medicine, 2014For testing the efficacy of a treatment in a clinical trial with survival data, the Cox proportional hazards (PH) model is the well‐accepted, conventional tool.
Harlan Campbell, C. Dean
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The Cox Proportional Hazards Model
2016The proportional hazards (PH) or Cox model holds on E, if the hazard rate has the form $$\begin{aligned} \lambda _{x(\cdot )}(t) = r\{x(t)\} \;\lambda _0(t), \quad x(\cdot ) \in E, \end{aligned}$$ where \(\lambda _0(\cdot )\) is an unspecified baseline hazard rate function , and \(r(\cdot )\) is a positive function on E. The function \(r(\cdot )\
Hong-Dar Isaac Wu, Mikhail Nikulin
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Jackknife for the proportional hazards model
Journal of Statistical Computation and Simulation, 1992Several jackknife methods for the proportional hazards model are proposed. Instead of deleting observations in the calculation of the pseudovalues, we delete the conditional probabilities from the partial likelihood function. The parameter estimators and variance estimators for both the linear and weighted linear jackknife methods are strongly ...
Wei-yann Tsai, Hui Quan
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