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

Detailed information about this course:

Description

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

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

Important: this course has a pre-course preparation module with a workload of 4-10 hours, which you must finalize prior to the course.

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.

See 'how to apply' for the course registration period.

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