Example 7.38: Kaplan-Meier survival estimates

May 24, 2010

(This article was first published on SAS and R, and kindly contributed to R-bloggers)

In example 7.30 we demonstrated how to simulate data from a Cox proportional hazards model.In this and the next few entries, we expand upon support in R and SAS for survival (time-to-event) models. We’ll start with a small, artificial dataset of 19 subjects. Each subject contributes a pair of variables: the time and an indicator of whether the time is when the event occurred (event=TRUE) or

To leave a comment for the author, please follow the link and comment on their blog: SAS and R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Tags: , , , ,

Comments are closed.


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)