Cox regression modelautomatic knots selectionspline basis expansionoptimizationRecently the shape-restricted inference has gained popularity in statistical and econometric literature to relax the linear or quadratic covariate effect in regression analyses. The typical shape-restricted covariate effect includes ...
In survival analysis, the well-known Cox regression is based on modeling the hazard rate. This method assumes a proportional hazard structure. Aalen's additive model, however, assumes a linear parametric structure on the hazard rate. This approach may be justified within counting process theory, ...
Cox modelLASSOrisk factorssurvival timesExisting models for coronary heart disease study use a set of common risk factors to predict the survival time of the disease, via the standard Cox regression model. For complex relationships between the survival time and risk factors, the linear regression ...
The partly linear additive Cox model is an extension of the (linear) Cox model and allows flexible modeling of covariate effects semiparametrically. We study asymptotic properties of the maximum partial likelihood estimator of this model with right-censored data using polynomial splines. We show that...
Cox proportional hazard model is a popular choice in modeling the survival data, but sometimes proportionality assumption is not satisfied. One of the tools for handling the non-proportional effects is the multiplicative-additive model named "Cox-Aalen model". Recently these flexible regression models...
data-sciencehazardsurvival-analysissurvivallifelinehazard-ratioskaplan-meiercox-regressionadditive-modelslog-rank-testsurvival-regressionkaplanmeierfittermultiplicative-model UpdatedAug 27, 2022 Jupyter Notebook Python implementations of semiparametric statistical techniques. ...
Model selection in competing risks regression In the analysis of time-to-event data, the problem of competing risks occurs when an individual may experience one, and only one, of m different types of e... D Kuk,R Varadhan - 《Statistics in Medicine》 被引量: 69发表: 2013年 Applying comp...
Understanding the Cox Regression Models With Time-Change Covariates The Cox regression model is a cornerstone of modern survival analysis and is widely used in many other fields as well. But the Cox models with time-change ... M Zhou - 《American Statistician》 被引量: 64发表: 2001年 Attenua...
With logistic regression, one needs the assumption that the odds ratio approximates relative risk to remove the dependence on the covariates of the test and of the measures of departure from additivity. However, this problem and other difficulties disappear with a Cox proportional hazards model, ...
Regression models for survival data have traditionally been based on a proportional hazards model, the most common being the Cox model (Cox 1972). The survival times of each individual is assumed to follow its own hazard function, h i