Multivariate Cox proportional hazard model for OS1.Juana, DornbuschAristeidis, ZacharisMatthias, MeinhardtKati, ErdmannIngmar, WolffMichael, FroehnerManfred, P. WirthStefan, ZastrowSusanne, Fuessel
Moreover, it is observed that the proposed multivariate proportional reversed hazard model can be obtained from the Marshall鈥揙lkin copula. The multivariate proportional reversed hazard models also have a singular component, and their marginals have proportional reversed hazard distributions. The ...
Cox proportional hazards modelling is a widely used method of analysing failure time data for indep... J Monaco,J Cai,J Grizzle - 《Statistics in Medicine》 被引量: 25发表: 2005年 Simplified modeling strategies for surrogate validation with multivariate failure-time data The linear mixed effects...
In the PH framework, it may be clear that none of the parametric models suggested here or elsewhere adequately capture the distributional form of the data. In such cases, the more flexible Cox model is the obvious choice. Commonly used parametric models in the AFT framework are arguably more ...
To take into account the dependence of the failure times within the unit (the individual or the cluster) as well as censoring, two multivariate generalizations of the Cox proportional hazards model are commonly used. The marginal hazard model is used when the purpose is to estimate mean ...
Sun Y, Gilbert PB, McKeague IW (2009) Proportional hazards models with continuous marks. Ann Stat 37(1):394–426. doi:10.1214/07-AOS554 Article MathSciNet MATH Google Scholar Sun Y, Li M, Gilbert PB (2013) Mark-specific proportional hazards model with multivariate continuous marks and...
A multivariate linear mixed sub-model is specified for the longitudinal outcomes, and a Cox proportional hazards regression model with time-varying covariates is specified for the event time sub-model. The association between models is captured through a zero-mean multivariate latent Gaussian process....
In particular, we discuss empirical likelihood results for a general mean functional of the distribution function, a functional of the hazard function, the Cox proportional hazards model, and a semiparametric accelerated failure time model... L Gang,R Li,Z Mai 被引量: 28发表: 2005年 Information...
A multivariate linear mixed sub-model is specified for the longitudinal outcomes, and a Cox proportional hazards regression model with time-varying covariates is specified for the event time sub-model. The association between models is captured through a zero-mean multivariate latent Gaussian process....
The methods we present here may be divided into two broad categories: proportional hazard approaches (including the semiparametric Cox model and fully parametric approaches) and accelerated failure time models. These methods have different properties and interpretations, but all may be used to summarise...