The pathway includes the following courses
Access is provided for 12 months, with code clinics provided throughout the year
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Introduction to R for Health Economic Evaluation
CourseThis course provides an introduction to R and RStudio for those new to the language who would like a gradual introduction before progressing onto the more advanced modelling and data-science for HEOR materials.
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State Transition (Markov) Models in R
CourseThis course teaches delegates to build a custom state transition model in base R. It uses an example model with time dependent transition probabilities, events and tunnel states. We also show how to run OWSA, PSA and VOI analyses.
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Pre-order available now!
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Partitioned Survival Models in R
CourseThis course teaches delegates to build a custom partitioned survival model in R. We also show how to run OWSA, PSA and VOI analyses.
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Efficient Microsimulation Modelling in R
CourseThis course teaches delegates to build microsimulation models in base R. It shows how to use vectorization, parallelization and C++ integration (through Rcpp) to considerably improve the run-time of microsimulation models.
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Making Health Economic Models Shiny
CourseThis course teaches delegates to create interactive web applications for health economic models. Based on peer reviewed literature, it shows how to develop robust and fast decision models, and deploy shiny user-interfaces written in R.
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Data Visualisation for Health Economic Evaluation
CourseThis course covers the skills necessary to create customised visuals for health economic evaluation. It focuses on the use of the ggplot2 package to make cost-effectiveness acceptability curves (CEACs), planes (CE-Planes) and Tornado Diagrams.
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Why use R for Health Economic Evaluation?
Instructors
Robert Smith, PhD
Dark Peak Analytics | University of Sheffield
Rob is an expert in the use of R for health economic modelling. He has previously worked at the UK Joint Biosecurity Centre, the UK Health Security Agency, the World Health Organization and The University of Sheffield. He has consulted for a wide range of organisations including top 10 pharmaceutical companies, national health ministries and HTA bodies. He is a keen proponent of the use of R for HTA; serving as co-director of the international R-HTA consortium and the World Health Organisation’s Health Economic Assessment Tool Expert Advisory Group.
Dr Paul Schneider, PhD
Dark Peak Analytics
Paul is an expert in the development of software for HEOR. A medical doctor and epidemiologist by training, he has used R on various research projects, ranging from the modelling costs of breast cancer, and value of information analyses, to the monitoring of influenza in real-time using online data. He is a keen advocate of open science practices and has published several open-source papers with Rob on the use of shiny and R for health economic evaluation.
Felicity Lamrock, PhD
Queens University Belfast | National Centre for Pharmacoeconomics
Felicity is Programme Director for the MSc in Data Analytics at Queens University Belfast and a Statistical Advisor to the National Centre for Pharmacoeconomics. As well as teaching, Felicity has published tutorial papers on the use of R for health economic evaluation, and is a co-director of R-HTA consortium.
Testimonials
Feedback from previous courses
“The course was great! The slides and explanations were clear. The exercises with solutions were really helpful, and loads of example code were made available. Having access to the recordings and the online book made the whole learning experience easier. ”
Dr Rami Cosulich, Research Associate, University of Sheffield
“The main tutor Rob was an excellent teacher, very knowledgeable and explains things very clearly at a good pace. The course material and resources were also excellent. I would thoroughly recommend and endorse this course.”
Dr Louise Linsell, Principal Statistician Visible Analytics
“The Dark Peak Analytics team is second to none. Very helpful, insightful, and friendly. Would highly recommend to anyone wanting to advance their HEOR skillsets in R. ”
Dr Michael Kim, Takeda/UIC
“Really accessible, loved the content with practice questions. This made it far less daunting for a complete beginner like myself.”
Delegate from NHS Scotland
“It was easy to follow, every material was easily accessible and it was structured in a very manageable way.”
Delegate from the University of Sheffield
“The course delivery has been great! I particularly appreciate the live and updated content and the accompanying coursebook.”
Delegate from GSK
“Thank you! I really enjoyed the course. I found having the textbook super helpful to read ahead of sessions, and the code clinics were useful to be able to more freely ask questions. The facilitators were so really good and appreciated their responsiveness to questions and comments in the chat. Impressed about live coding skills!”
Delegate from Dept. for Health and Social Care, UK
“The format worked well (mix of taught sessions and code clinics), tutors were all great and very knowledgeable and engaging. Really appreciated being able to get feedback on my code. I've come away feeling a lot more confident, and also of how much left I have to learn.”
Delegate from FTSE100 Pharma
“This course was the best training I’ve attended. It covered many areas essential to understanding the content, including how to structure your model, vectorization, a variety of needed commands and their efficiency, creating custom functions, combining functions to create a model, plotting data, and so much more.”
Aaron Winn, Associate Professor University of Illinois
“This microsimulation in R is really well structured and informative course. Especially, they provide you a bunch of codes that you can run on your own program. I definitely recommend this course to those who are interested in applying this knowledge to their study. ”
Sodam Kim, University of Illinois
Bundle Prices
Save 25% by booking all of the courses as a bundle.
FAQ
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What is the time commitment required?
Delegates will need to average around 2-3 hours a week across a 12 month period, or more if the course is taken over a shorter duration.
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Can we choose when to have the code clinics?
When booking the bundle delegates can join any of the live sessions advertised, or can arrange a 1 hour 1-2-1 session.
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How long will I have access to course materials for?
For 12 months. Some of our materials are also downloadable, so you can still refer to them after that period.
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What software do delegates need on their computer?
To run the code provided, we recommend delegates have R Version 4.0.2 (2020-06-22) or newer, and RStudio (https://www.rstudio.com/products/rstudio/download/)
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I want something more bespoke, do you teach other courses?
Yes, we teach bespoke courses on a range of other topics in addition to teaching these topics in live sessions within Industry, Universities and Government.
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What kinds of questions can we ask in the code clinic?
Anything you like. We will prioritise questions about the course materials, but feel free to bring any other challenges you are facing (related to R or Health Economics).
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Do you give a discount for the bundle for those from LMIC
The bundle has a 33% discount applied to all delegates. To enquire about a further discount please email us.