glmnet v4.1: regularized Cox models for (start, stop] and stratified data

[This article was first published on R – Statistical Odds & Ends, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

My latest work on the glmnet package has just been pushed to CRAN! In this release (v4.1), we extend the scope of regularized Cox models to include (start, stop] data and strata variables. In addition, we provide the survfit method for plotting survival curves based on the model (as the survival package does).

Why is this a big deal? As explained in Therneau and Grambsch (2000), the ability to work with start-stop responses opens the door to fitting regularized Cox models with:

  • time-dependent covariates,
  • time-dependent strata,
  • left truncation,
  • multiple time scales,
  • multiple events per subject,
  • independent increment, marginal, and conditional models for correlated data, and
  • various forms of case-cohort models.

glmnet v4.1 is now available on CRAN here. We have reorganized the package’s vignettes, with the new functionality described in the vignette “Regularized Cox Regression” (PDF version/web version). Don’t hesitate to reach out if you have questions.

(Note: This is joint work with Trevor Hastie, Balasubramanian Narasimhan and Rob Tibshirani.)

To leave a comment for the author, please follow the link and comment on their blog: R – Statistical Odds & Ends. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)