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Course curriculum

Learn how to calibrate natural history of disease models in R. Aimed at health economists and epidemiologists interested in learning practical calibration skills for simulation models.

    1. Welcome

    2. Code download

    3. Coursebook

    4. Prerequisites & Key Resources

    1. Objectives

      FREE PREVIEW

    2. Content Overview

    3. Objects Presentation

    4. Objects Quiz

    5. Objects Code Walkthrough

    6. Objects Exercise

    7. Functions Presentation

    8. Functions Quiz

    9. Functions Code Walkthrough

    10. Functions Brainteaser

    11. Functions Exercise

    12. Loops & Iterations Presentation

    13. Loops Code

    14. Loops Quiz

    15. Loops Exercise

    16. Lapply Code

    17. Iteration Quiz

    18. Iterations Exercise

    19. Code Optimisation

      FREE PREVIEW

    20. Code Optimisation Quiz

      FREE PREVIEW

    21. Additional Resources

    1. Content Overview

    2. Foundations of model calibration

    3. Quiz 1.1:

    4. * Optional: Natural history and screening targets

    5. * Optional: Quiz 1.2:

    6. The seven-step calibration framework

    7. Quiz 1.3:

    8. The teaching model

    9. Quiz 1.4:

    10. Exercise 1.1: Run and inspect the cancer relative-survival model

    11. Exercise 1.2: Run and inspect the hypothetical infectious-disease model

    1. Content Overview

    2. Anatomy and goodness of fit

    3. Quiz 2.1:

    4. Unguided search

    5. Quiz 2.2:

    6. Directed search

    7. Quiz: 2.3:

    8. Uncertainty and choosing a method

    9. Quiz 2.4:

    10. Exercise 2.1a: CRS unguided search and acceptance

    11. Exercise 2.1b: CRS directed search and local uncertainty

    12. Exercise 2.2: Transfer non-Bayesian calibration to the HID model

    1. Content Overview

    2. Bayesian calibration: from targets to a posterior

    3. Quiz 3.1:

    4. Metropolis-Hastings calibration

    5. Quiz 3.2:

    6. Hamiltonian Monte Carlo and NUTS

    7. Quiz 3.3:

    8. Sampling-importance resampling

    9. Quiz 3.4:

    10. Incremental Mixture Importance Sampling

    11. Quiz 3.5:

    12. BayCANN concepts

    13. Quiz 3.6:

    14. Implementing BayCANN

    15. Quiz 3.7:

    16. Comparing and choosing methods

    17. Quiz 3.8:

    18. Exercise 3.1a: CRS Random-Walk Metropolis tuning

    19. Exercise 3.1b: CRS SIR and weight degeneracy

    20. Exercise 3.2: Transfer Bayesian calibration to the HID model with IMIS

    1. Content Overview

    2. Approximate Bayesian computation

    3. Quiz 4.1:

    4. Rejection ABC

    5. Quiz 4.2:

    6. ABC-MCMC

    7. Quiz 4.3:

    8. Incremental Mixture ABC

    9. Quiz 4.4:

    10. Comparing the three ABC methods

    11. Quiz 4.5:

    12. Exercise 4.1a: CRC rejection-ABC tolerance sensitivity

    13. Exercise 4.1b: CRC ABC-MCMC proposal scale and mixing

    14. Exercise 4.1c: CRC microsimulation cohort size

    15. Exercise 4.2: Transfer ABC-MCMC to the HID model

About this course

  • 89 lessons
  • Online Coursebook
  • 6 x 1 hour live code clinics
  • Exercises & solutions


What's included

Follow at your own pace, with extensive course materials, code demos and exercises. Bespoke live sessions available - get in touch to find out more.

  • Online coursebook with step by step guides to undertaking calibration in R

  • Recorded presentations covering the key concepts, and with step by step code walkthroughs

  • Code repository containing all code from the demonstrations, exercises and solutions

  • Live code clinics made available at set intervals during the year. Please check the schedule for more information.


Instructors

Wael Mohammed, PhD

Dark Peak Analytics | University of Sheffield

Wael has a background in pharmacy and public health. He is an expert in decision-analytic modelling, econometrics, and data science (especially in R). He has a PhD in calibration methods for health economic evaluation from the University of Sheffield. He has previously held positions at, NICE, the Department for Health and Social Care and the University of Sheffield.

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.


View our upcoming code clinic schedule below

Schedule


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


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Join us to access the course materials & live code clinics

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    Content + Live Code Clinics

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FAQ

  • Do you offer live Q&A sessions for this course?

    Yes, please check the 'Live Schedule' page for more information on live sessions.

  • 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.

  • When are the course materials made available?

    Course materials are provided immediately

  • What software do I need on my computer?

    To run the code provided, we recommend delegates have R Version 4.0.2, and RStudio. You will also need to install Git and create an account on GitHub. This is described in the course.

  • 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. For our full pathway see https://www.courses.darkpeakanalytics.com/bundles/r4he-modelling-skills

  • Will I get an invoice?

    Yes, you'll receive an invoice by email after booking.

  • Do you provide discounts for LMIC?

    Yes, we offer a discount for those booking from a LMIC. Please use the discount code: lmic25 for a 25% discount.

  • Can I book for a large group? Do you offer discounts for large groups?

    It is possible to book for others using a 'gift' purchase. We do offer discounts for large group bookings, please contact us to get a booking link.