Epidemiologic Analysis Using R

Monday, June 4, 2018 - Friday, June 8, 2018 8:30 AM - 12:30 PM

Download the syllabus for this course

Download the flyer for this course


Space is for this course is limited! Register now!

Course Description

This course will teach public health researchers and epidemiologists how to use the R statistical computing platform to do epidemiologic analysis. The material is intended for students or practitioners who want to use R to apply the basic epidemiological or biostatistical methods they have learned or are currently learning. Participants will construct, manipulate, and analyze data objects, addressing issues commonly encountered in epidemiologic research.

The overall goal is to introduce students to programming skills so they can (1) develop their own tools to apply epidemiologic methods, and (2) use those tools to answer epidemiologic questions.

Course Objectives

By the end of the course, participants will be able to:

  1. Understand R data objects and how they relate to common epidemiological tasks
  2. Know how to read in, index and manipulate data objects in R
  3. Calculate rates, ratios, risks and their associated confidence intervals and p values in R
  4. Plot simple graphics
  5. Write their own R functions
  6. Find, install, and use R packages for other tasks not explicitly covered in class


Students should plan to bring their own laptops.

Course Reading List



Stephanie Shiau, PhD, MPH

Dr. Stephanie Shiau is a Postdoctoral Research Scientist at the Gertrude H. Sergievsky Center at Columbia University Medical Center. Her primary research interests lie at the intersection of lifecourse epidemiology and HIV. She currently studies the timing of antiretroviral treatment initiation in HIV-infected infants and children, growing up and aging with HIV, and HIV-associated non-AIDS (HANA) conditions. Dr. Shiau holds a BA in Public Health Studies from The Johns Hopkins University and an MPH and PhD in Epidemiology from Columbia University. She has several years of experience conducting data analysis with and teaching both SAS and R.

Course Fee

Registration for this course is $900.00



The registration period has closed for this event.


Share This