A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model [PDF]
There have been few investigations of cancer prognosis models based on Bayesian hierarchical models. In this study, we used a novel Bayesian method to screen mRNAs and estimate the effects of mRNAs on the prognosis of patients with lung adenocarcinoma ...
Na Sun +5 more
doaj +3 more sources
Moving beyond the Cox proportional hazards model in survival data analysis: a cervical cancer study [PDF]
Objectives This study explored the prognostic factors and developed a prediction model for Chinese-American (CA) cervical cancer (CC) patients. We compared two alternative models (the restricted mean survival time (RMST) model and the proportional ...
Lixian Li +3 more
doaj +3 more sources
Gradient lasso for Cox proportional hazards model [PDF]
AbstractMotivation: There has been an increasing interest in expressing a survival phenotype (e.g. time to cancer recurrence or death) or its distribution in terms of a subset of the expression data of a subset of genes. Due to high dimensionality of gene expression data, however, there is a serious problem of collinearity in fitting a prediction model,
Insuk, Sohn +3 more
openaire +3 more sources
Reasons why osteoarthritis predicts mortality: path analysis within a Cox proportional hazards model [PDF]
Objectives To identify potentially modifiable factors that mediate the association between symptomatic osteoarthritis (OA) and premature mortality.Methods A population-based prospective cohort study; primary care medical record data were linked to self ...
George Peat +7 more
doaj +2 more sources
Adjusting for bias introduced by instrumental variable estimation in the Cox Proportional Hazards Model [PDF]
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) procedure ...
Goodney, Philip P. +4 more
core +2 more sources
Data generation for the Cox proportional hazards model with time-dependent covariates: A method for medical researchers [PDF]
The proliferation of longitudinal studies has increased the importance of statistical methods for time-to-event data that can incorporate time-dependent covariates. The Cox proportional hazards model is one such method that is widely used.
Hendry, David J.
core +2 more sources
Fitting the Cox proportional hazards model to big data. [PDF]
AbstractThe semiparametric Cox proportional hazards model, together with the partial likelihood principle, has been widely used to study the effects of potentially time-dependent covariates on a possibly censored event time. We propose a computationally efficient method for fitting the Cox model to big data involving millions of study subjects ...
Wang J, Zeng D, Lin DY.
europepmc +3 more sources
Adaptive Lasso for Cox's proportional hazards model [PDF]
SUMMARY We investigate the variable selection problem for Cox's proportional hazards model, and propose a unified model selection and estimation procedure with desired theoretical properties and computational convenience. The new method is based on a penalized log partial likelihood with the adaptively weighted L1 penalty on regression coefficients ...
Hao Helen Zhang, Wenbin Lu
openaire +3 more sources
Variable Selection for Cox's proportional Hazards Model and Frailty Model
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fan, Jianqing, Li, Runze
openaire +3 more sources
A flexible alternative to the Cox proportional hazards model for assessing the prognostic accuracy of hospice patient survival. [PDF]
Prognostic models are often used to estimate the length of patient survival. The Cox proportional hazards model has traditionally been applied to assess the accuracy of prognostic models.
Branko Miladinovic +5 more
doaj +2 more sources

