Contents
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 use method lasso in Cox model?
Each times I get Error in coxnet (x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, : negative event times encountered; not permitted for Cox family. can anyone help me solve this problem ?
How is cv.glmnet used in Cox regression?
The function cv.glmnet can be used to compute K -fold cross-validation (CV) for the Cox model. The usage is similar to that for other families except for two main differences. First, type.measure only supports “deviance” (also default) which gives the partial-likelihood, and “C”, which gives the Harrell C index.
How to use model selection through shrinkage ( LASSO )?
Closed 3 months ago. I would like to use model selection through shrinkage (Lasso) using glmnet. So far I did the following:
How to use method lasso in Cox model using glmnet?
I have the survival data includes 252 patients, 25 independent variables and 35 events. I want to use lasso method in cox model to these data. I use glmnet for it. but, I encountered an error which I cannot explain or solve.
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.
Are the lasso coefficients interpreted in the same way as the OLS maximum likelihood?
Let me rephrase: Are the LASSO coefficients interpreted in the same way as, for example, OLS maximum likelihood coefficients in a logistic regression? LASSO (a penalized estimation method) aims at estimating the same quantities (model coefficients) as, say, OLS maximum likelihood (an unpenalized method).