Year Published: 2013

Time to Complete: 75 min

Instructor: Robin Ruthazer, MPH

Learning Level: Fundamental

Primary Audience: Researchers

Prerequisite: None

Skills Domain: Scientific Concepts and Research Design


Wondering how patient survival data is analyzed in clinical research?

Have you always wondered how survival estimates are calculated?

In this course, Statistician Robin Ruthazer, MPH, will present a behind-the-scenes look at survival analysis. Learn how time-to-event data requires special techniques like Kaplan-Meier curves and Cox regression, and how their output is interpreted.

Learning Objectives

After completing this course, you will be able to:

  • Define survival analysis
  • Explain how time-to-event data is different from other data
  • Discuss the differences between Kaplan-Meier curves and Cox regression
  • Identify a Kaplan-Meier curve and a Cox regression in a journal article
  • Describe how survival estimates are calculated

Content Outline

  • What is a Survival Analysis
  • Censoring
  • Objectives of Survival Analysis
  • Choice of Time Origin
  • Survival Analysis Data Structure
  • Kaplan Meier Estimate of Survival
  • Example Kaplan Meier Plot Comparing Treatment & Placebo Groups for Leukemia Patients
  • Comparing Survival Between Groups
  • Kaplan Meier Estimate of Survival
  • Cox Regression
  • Proportional Hazards Model
  • Model Building Strategies
  • Time Dependent Variables
  • Competing Risks

Resources

  • Lecture Slide Deck (PDF)

Course Evaluation

  • Post-Course Evaluation
  • Course Completion Verification
 This Course is Free