The simple proportional hazards model
Adaptive-LASSO for Cox's proportional hazards model
... Bayesian variable selection for survival data was investigated by Faraggi & Simon (1998) and Ibrahim, Chen & MacEachern (1999). However, the theoretical properties of these methods are generally unknown (Fan & Li 2002). ...
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The Dantzig selector in Cox's proportional hazards model
... The data sets described above were generated 50 times, and randomly split into training and test sets with a 7:3 ratio. The survival prediction methods were applied to the training sets, and the test set was then used ...
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Application Of The Empirical Likelihood Method In Proportional Hazards Model
... Our proposed approach is computationally simple. Along with the construction of the test, we provide a consistent semi-parametric maximum likelihood estimator for β 0 under model assumption (61) for two ...
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Estimating proportional hazards model using frequentist and bayesian approaches
... of proportional hazards model has become computationally feasible due to modern technology and advancement in computing techniques such as the Gibbs sampler and other MCMC ...considered simple ...
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On the proportional hazards model for occupational and environmental case-control analyses
... and simple selection prob- abilities that did not reflect the more complex sampling scheme of population-based case-control ...WC model, as compared with stand- ard logistic regression analyses, for ...
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A proportional hazards model for time-to-event data with epidemiological bias
... and the average standard deviation estimates (ˆ σ β ) for the proposed estimates of ˆ β are reported. The tables also present the coverage probabilities of 95% confidence intervals constructed based on the normal ...
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Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent
... 4. Discussion We have shown cyclical coordinate descent to be a very efficient algorithm for maximizing the partial likelihood with the elastic net penalty. Each coordinate step has a simple, closed form solution. ...
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Small sample confidence bands for the survival functions under proportional hazards model
... was originally proposed by Kaplan and Meier (1958) and is perhaps the most commonly used estimator of S (t) with right censored data. In addition, ˆ S KM (t) satisfies the self- consistency equations from Efron (1967) and ...
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Estimation in a Competing Risks Proportional Hazards Model Under Length-biased Sampling With Censoring
... the simple fact that, when drawing observations from a set of subjects in a particular state, the probability of being included in the sam- ple is proportional to the sojourn time in that ...
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Proportional Hazards Regression Model for Time to Event Breast Cancer Data: A Bayesian Approach
... The proposed Bayesian method was used to fit the survival models for non-informative right censored breast cancer data. The results which are presented in this paper followed the trend and in fact it showed the reality. ...
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A Statistical Model with Non Linear Effects and Non Proportional Hazards for Breast Cancer Survival Analysis
... Non-Proportional Hazards Using Time Varying Effects Model The common method that is used to account for non-proportionality in a cova- riate is stratification, that is, use of the proportional ...
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Data generation for the Cox proportional hazards model with time-dependent covariates: A method for medical researchers
... tional hazards model is one such method that is widely ...Cox model with time-dependent covariates are developed, simulations studies will grow in impor- tance as ...Cox proportional ...
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The Cox Proportional Hazards Model
... effect of interest (i.e., not the treatment variable) and it does not interact with the effect of interest.. Time-dependent covariates[r] ...
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Estimation in a Cox Proportional Hazards Cure Model
... We develop maximum likelihood techniques for the joint estimation of the incidence and latency regression parameters in this model using the nonparametric form of th[r] ...
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On the dependence between the extreme order statistics in the proportional hazards model
... where (S, T ) represents any concordance measure between random variables S and T in the sense of Scarsini [16], e.g., Spearman’s rho or Kendall’s tau. This result is established under the assumption that X 1 , . . . , ...
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False Selection Rate Methods in the Cox Proportional Hazards Model
... Table 4.2 summarizes the average b λ estimated by GCV in the original LASSO method and by the LASSO-FSR method on data sets with sample size 150 and 12 covariates. We see that b λ chosen by GCV is relatively smaller than ...
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Semiparametric estimation of a panel data proportional hazards model with fixed effects
... duration model that has a proportional hazards spec- ification with fixed ...the proportional hazards model with dependent right censoring, under which the partial likelihood ...
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Marginal structural Cox proportional hazards model for data with measurement errors
... Cox model proposed by Robins ( 1998 ) with the regression calibration method proposed by Rosner et ...Cox proportional haz- ards model using the self-reported treatment assignments as the predictor ...
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A Gamma-frailty proportional hazards model for bivariate interval-censored data
... Table 1 also summarizes the parameter estimates arising from the two competing techniques; i.e., the univariate and marginal methods. From these results one will note that the two competing techniques perform well, but ...
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A multi-stage stochastic programming for condition-based maintenance with proportional hazards model
... to model CBM of a system for a finite planning horizon in which the state of the system or covariate value constituting PHM was an uncertain parameter at each inspection point or ...the model as a ...
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