Using R for Decision Modeling in Health Technology Assessment [EL005]

Course highlights

EC points

1.7

Start date

07-02-2022

End date

11-02-2022

Course days

Weekdays

Faculty

Petros Pechlivanoglou, PhD, Eline Krijkamp, PhD

Course fee

€ 860

Location

Online

Level

Advanced

Prerequisites

To benefit from this course students should have:

  • Basic probability and statistics knowledge AND
  • Some experience with R coding (has done NIHES courses using R (CK020, courses of Dr. Rizopoulos using R) or online courses like DataCamp) or significant experience with coding in other programming languages, AND
  • Successfully passed an advanced course in decision modeling:
    • EL004: Advanced Topics in Decision Making in Medicine
    • Harvard T.C. Chan School of Public health courses RDS202, RDS280, RDS286
    • Faculty approval of an equivalent course
  • Recommended but not compulsory: Using R for Statistics in Medical Research (CK020)

Disciplines

  • Clinical Epidemiology

Application

How to apply

Detailed information about this course:

Description

This course aims to teach how to build decision models in R to students who have a basic understanding of health decision science.

  • The course combines lectures with R coding exercise.
  • The course is project-based. You are encouraged to apply the theory and skills you learn during this course to a decision problem you select yourself.

More detailed information about each session will be provided in the syllabus.

Attendance of all lectures and practicums is compulsory in order to be able to complete the assignments and case example successfully. Each day builds on knowledge and skills from the previous day. Clarification of the material taught is best done in the interactive teaching environment provided during classroom sessions.

Objectives

By the end of the course the student will be able to

  • Create decision models using R (decision tree/cohort/microsimulation models)
  • Understand the advantages and disadvantages of building decision models in R
  • Apply good coding practice in R
  • Create transparent and readable decision models
  • Apply the methods learned in real-life practical examples

Participant profile

Students (Msc/PhD level) or researchers in decision science, health economics, clinical sciences, clinical epidemiology, public health, health technology assessment or value-based healthcare.

Assessment

Assignment(s), Attendance


Reduction on fees

PLEASE NOTE THIS DOES NOT APPLY TO THE RESEARCH MASTERS (120 EC points)

No fees are charged for participation of Erasmus MC PhD candidates

Please note that in case of cancellation or no show, the cancellation policy applies based on the full course fee.

 

25% reduction for all (international) PhD students without formal appointment at Erasmus MC

Upon receipt of your application you will receive a request to upload proof of enrollment as a PhD student.