hazards model
Estimating proportional hazards model using frequentist and bayesian approaches
... Modelling and survival data analysis is one of the oldest fields in statistics. Generally, survival data deals with lifetimes from some initial event at time zero to some terminal event of interest and basically the data ...
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Survival Analysis of Determinants of Breast Cancer Patients at Hossana Queen Elleni Mohammad Memorial Referral Hospital, South Ethiopia: Bayesian Application of Hypertabastic Proportional Hazards Model
... the model with smaller value fit the data ...Proportional Hazards Model has smaller criterion values as compared to Cox Proportional Hazards Model and it better fits the data on breast ...
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False Selection Rate Methods in the Cox Proportional Hazards Model
... We wrote SAS programs (Software SAS version 9.1) to implement the first five meth- ods. The other seven methods are computed in MATLAB (Software MATLAB version 7.0), using programs received from Runze Li on September 9, ...
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Parametric Cure Model versus Proportional Hazards Model in Survival Analysis of Breast Cancer and Other Malignancies
... It is generally assumed that, provided the proportional hazards model holds, the proportion of patients cured (i.e., saved from the event) can be estimated by 1-HR [3-5], which in turn is calculated from ...
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The single-index hazards model
... proportional hazards model in which a single-index was used for dimension reduction and Xia et ...general model which includes the transformation model (Zeng and Lin 2007b) and the accelerated ...
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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 ...proportional hazards model with dependent right censoring, under which the partial likelihood estimator is ...
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Adaptive-LASSO for Cox's proportional hazards model
... Recently a family of penalized partial likelihood methods, such as LASSO (Tibshirani 1997) and SCAD (Fan & Li, 2002), have been proposed for Cox’s proportional hazards model. These methods shrink some ...
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On the proportional hazards model for occupational and environmental case-control analyses
... WC model is an alternative method for estimating the effects of time-varying exposure variables in case-control ...WC model tended to provide more accurate estimates of the effects of variables for which an ...
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A semiparametric Bayesian proportional hazards model for interval censored data with frailty effects
... Another, more general methodology with similar ingredi- ents has been published by Hennerfeind, Brezger and Fahrmeir [17]. In their work, Hennerfeind et al. do not consider explicitly interval censoring, however this is ...
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Survival Analysis in LGL Modelling for Retail Mortgage Portfolios
... Cox model, we tested the effects of time-dependent explanatory variables on the baseline survival ...non-performing model. It is not possible to develop a time- dependent performing model because no ...
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Analysis of Influencing Factors on Survival Time of Patients with Heart Failure
... In clinical practice, some subjects may be observed more than once during the time from first hospitalization to death. The number of hospitalizations and the days between two hospitalizations varies from patient to ...
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Additive-multiplicative hazards regression models for interval-censored semi-competing risks data with missing intermediate events
... proportional hazards model with the additive risk model of [16], in accordance with a multi-state ...additive-multiplicative model was initially introduced by [17] and has since been devel- ...
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A Bayesian Approach to Exemplify the Identification Problem in Discrete-time Hazards Models with Multiple Interactions
... Abstract The aim of this study is to discuss the weakness of the conventional way of presenting the relative intensities in multiplicative models. The identification problem in hazards models with multiple ...
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Bayesian Spatial Additive Hazard Model
... The era of statistical modeling based on marginal analysis is almost coming to an end in the face of increasing demand to analyze complex, multidimensional and correlated streams of data that are available to ...
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Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization
... proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients ’ clinical ...
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nihms842809.pdf
... proportional hazards model for clustered event data. The model incorporates the unknown threshold of a continuous variable as a change point in the ...
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Wogu_unc_0153D_19640.pdf
... proportional hazards model is the additive hazards model, which estimates the difference in ...subdistribution hazards model in the presence of competing risks in case-cohort ...
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The relationship between high-dose corticosteroid treatment and mortality in acute respiratory distress syndrome: a retrospective and observational study using a nationwide administrative database in Japan
... proportional hazards model in order to minimize the bias associated with the retrospective collection of data on baseline characteristics and compared the mortality between the high-dose and non-high-dose ...
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A Simple Stochastic Stomach Cancer Model with Application
... regression model and compared it with weibull, exponential and lognormal models to evaluate prognostic factors affecting survival of patients with stomach ...regression model to study patient specific ...
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A STUDY OF THE SLOPE OF COX PROPORTIONAL HAZARD AND WEIBULL MODELS: SIMULATED AND REAL LIFE DATA APPROACH
... Weibull model may be estimated in R- program with the SURVREG, an R package designed for simulation in survival analysis with Weibull Model as underlying distribution, which uses the MSE method as stated in ...
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