Using R for Decision Modeling in Health Technology Assessment [CE16]

Course highlights

EC points


Start date


End date


Course days

Weekdays, except Wednesday


Petros Pechlivanoglou, PhD, Eline Krijkamp, MSc

Course fee

€ 820


Erasmus MC, Rotterdam NL




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 (CC02, 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:
    • EWP02: 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 (BST02)


  • Clinical Epidemiology


How to apply

Detailed information about this course:


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 highly recommended 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.


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.


Assignment(s), Attendance

Reduction on fees


50% reduction on our fees for participating institutes of NIHES

This 50% reduction is offered to participants formally appointed at the departments or sections participating in NIHES.

University Medical Center Rotterdam/Erasmus University Rotterdam:

  • Department of Epidemiology
  • Department of Public Health
  • Department of Psychiatry, Section of Medical Psychology and Psychotherapy
  • Department of Child and Adolescent Psychiatry/Psychology
  • Department of Medical Informatics
  • Department of General Practice
  • Erasmus School of Health Policy & Management
  • Generation R

50% reduction on our fees for NIHES affiliated partners

This 50% reduction is offered to participants formally appointed at the following NIHES affiliated partners:

University Medical Center Rotterdam/Erasmus University Rotterdam, departments of:

  • Dermatology
  • General Paediatrics
  • Plastic and Reconstructive Surgery
  • Rehabilitation Medicine

UMIT, Department of Public Health, Health Services Research and Health Technology Assessment.

25% reduction on our fees for partner institutes of NIHES

For participants formally appointed at all departments of Erasmus MC (except the departments mentioned above).

25% reduction for all (international) PhD students
Please upload proof of enrollment as a PhD student in the application form and state the name of your tutor on the application form (remarks field).

25% reduction on our course fees (maximum 3 EC points per academic year) for all NIHES alumni
Please state that you are a NIHES alumnus/alumna and the academic year you graduated (remarks field). Please note that the reduction on fees for alumni does not apply to the Erasmus Summer Programme.