Contents
How to fit regularized Cox regression to glmnet?
“Regularized Cox Regression” describes how to fit regularized Cox models for survival data with glmnet. “GLM family functions in glmnet ” describes how to fit custom generalized linear models (GLMs) with the elastic net penalty via the family argument.
When to use glmnet for Cox proportional hazards?
This vignette describes how one can use the glmnet package to fit regularized Cox models. The Cox proportional hazards model is commonly used for the study of the relationship beteween predictor variables and survival time.
How to visualize survival curves in Cox regression?
Class “coxnet” objects have a survfit method which allows the user to visualize the survival curves from the model. In addition to the “coxnet” object, the user must pass the x and y objects used to fit the model (for computation of the baseline hazard), as well as the lambda value for which the survival curve is desired:
How are the survival curves returned in glmnet?
To be consistent with other methods in glmnet, if the s parameter is not specified, survival curves are returned for the entire lambda sequence. The survival curves are returned as a list, one element for each lambda value. The survfit method is available for cv.glmnet objects as well.
How are GLM family functions used in glmnet?
“GLM family functions in glmnet ” describes how to fit custom generalized linear models (GLMs) with the elastic net penalty via the family argument. “The Relaxed Lasso” describes how to fit relaxed lasso regression models using the relax argument. over a grid of values of λ covering the entire range of possible solutions.
How does glmnet return a sequence of models?
The function glmnet returns a sequence of models for the users to choose from. In many cases, users may prefer the software to select one of them.
Which is an extension of the Cox regression model?
One extension of the Cox regression model is to allow for strata that divide the observations into disjoint groups. Each group has its own baseline hazard function, but the groups share the same coefficient vector for the covariates provided by the design matrix x.