Learning Objectives

  1. Define main types of censoring
  2. Define the assumption of uninformative censoring
  3. Define survival function, hazard functions, cumulative event function
  4. Perform a Kaplan-Meier estimate
  5. Perform, interpret, and identify assumptions of the logrank test
  6. Define and calculate potential follow-up time
  7. Calculate median survival time


  1. Introduction to censored data
    • Outcome variable: time-to-event
    • Types of censored data
    • Assumption of uninformative censoring
  2. Survival function and Kaplan-Meier estimator
  3. Comparing groups: Log-rank test
  • Vittinghoff sections 3.1-3.5
  • Tutorial Paper Survival Analysis Part I: Basic concepts and first analyses by Clark, Bradburn, Love, Altman. British Journal of Cancer (2003) 89, 232 – 238


Learning Objectives

  1. Calculate Kaplan-Meier estimates of survival probability over time
  2. Plot survival curves for censored time-to-event data
  3. Perform and interpret log-rank test
  4. Define “informative” censoring


  1. Calculate the follow-up table for 6 MP patients in the leukemia study
  2. Plot the Kaplan-Meier estimate of the follow-up table from 1. library(survminer) is recommendable.
  3. What is the 75th percentile of survival times for the 6 MP group? For the Placebo group? This is the time that 75% of the patients survive.
  4. Suppose you were instructed to cap follow-up times at 20 weeks. Re-do the Kaplan-Meier plot for both groups, and re-do the logrank test.
  5. Give a hypothetical example of how censoring in this example might be “informative.”