Survival Analysis – 1

August 2, 2015
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(This article was first published on Just Another Data Blog, and kindly contributed to R-bloggers)

I recently was looking for methods to apply to time-to-event data and started exploring Survival Analysis Models. In this post, I’m exploring basic KM estimator which is a nonparametric estimator of the survival function using a real dataset (on time to death for 80 males who were diagnosed with different types of tongue cancer, from package KMsurv) and a simulated dataset (using package survsim). In addition I am using OIsurv, dplyr, ggplot2 and broom for this analysis.

Following is a basic rmarkdown document illustrating the analysis. In my future posts, I’m planning to explore more on following survival models –

  • Proportional hazards model
  • Accelerated failure time Model
  • Multiple events model (More than 2 possible events)
  • Recurring events (Each subject can experience an event multiple times).

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