| Website | https://www.frick.ws/ |
| Github | https://github.com/hfrick |
| Bluesky | https://bsky.app/profile/frick.ws |
Registration for tutorials at useR! in Salzburg is open! I'll be teaching an in-person tutorial on Survival Analysis with tidymodels with @topepo .To register for the tutorial, log back into your conference registration and then modify it to include tutorials (and maybe a social event!) in Step 4 "Reg Options." It's a bit of clicking to get there, but the choice of tutorials and social activities is worth it! #RStats #useR2024
To modify your registration: https://events.linuxfoundation.org/user/register/
A key component of the new tidymodels functionality for survival analysis are the new metrics. This post walks you through the Brier score and area under the ROC curve, as adapted for predictions of survival probability! #RStats
https://www.tidymodels.org/learn/statistics/survival-metrics/
We've released support for survival analysis in tidymodels. This methodology is useful for all kinds of time-to-event data: That event may be a customer churning, a machine needing repairs or replacement, a shelter animal being adopted, etc.
For a new case study on tidymodels.org, that event is a complaint to the NYC Departments of Buildings being dispositioned. The analysis shows how to use tidymodels for censored regression, covering the whole process. #RStats
https://www.tidymodels.org/learn/statistics/survival-case-study/
The flexsurv R package for flexible parametric survival and multi-state modelling - GitHub - chjackson/flexsurv: The flexsurv R package for flexible parametric survival and multi-state modelling
