Health economics modelling in R

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Karolinska Institutet and University College London will be hosting a course on health economics modelling in R.

Learn about health economics modelling and how to implement a range of models in R. The first day of the course will consist of lectures giving a grounding in health economics modelling for cost-effectiveness analyses from a Bayesian perspective. The second day of the course will consist of computer labs in which models presented in Day 1 are implemented in R.


Lecture topics


Required software (for day 2):

We suggest all participants attending day 2 bring a laptop on which they have installed R (along with the BCEA package) and OpenBUGS and/or JAGS.

Course faculty will assist you with the installation during the course if needed. Contact Enoch Yi-Tung Chen if you need help with installation prior to the course.


The following sets out a basic installation process:

If necessary download and install R and potentially a user interface to R like RStudio.

Download and install JAGS as per operating system requriements; and/or OpenBUGS.

Install additional R packages: e.g., in R install.packages("rjags") and install.packages("R2OpenBUGS").

Target audience

The course is open to everyone with an interest in health economics modelling. The primary target audience is researchers knowledgeable about statistical modelling who are interested in learning health economics modelling. That is, we assume participants have prior knowledge of statistics but do not assume prior knowledge of health economics.

Course certificate

Each participant will receive a certificate of attendance. There is no examination. The course is not an official university course and completion of the course does not automatically entitle academic credits.


Registration: Register via Google forms

Cost: No charge to participants

Please register before June 1st. Class size is limited on day 2 (hands-on computer exercises). If the course is oversubscribed, priority will be given to staff and students at Karolinska Institutet.

  • Program | topics: Cost-effectiveness analysis; R software

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