R for Health Technology Assessment

Bayesian statistics

Health economics

Author

Gianluca Baio, Howard Thom, Petros Pechlivanoglou

Published

July 1, 2025

R for Health Technology Assessment discusses the use of proper statistical software, specifically R, to perform the whole pipeline of analytic modelling in health technology assessment (HTA). It has been designed with the objective of establishing the use of R as the standard tool for HTA amongst academics, industry practitioners and regulators. It covers a lot of ground, starting with the necessary background in HTA, R and statistical inference, followed by various modelling tools, ranging from missing data, survival analysis and decision trees, through to multistate models and discrete event simulation. The methods are all illustrated with many detailed worked examples and case studies using real data, and there are detailed descriptions of the code and processes.

Important

The book is also freely available online (in html format only), here!

Table of content

Part 1: Preliminaries

Chapter 1: Introduction to Health Technology Assessment (Anna Heath, Gianluca Baio, Petros Pechlivanoglou)
Chapter 2: Introduction to R (Howard Thom, David Phillippo)
Chapter 3: Why R?: A Low- and Middle-Income Countries Perspective (Joshua Soboil, Federico Rodriguez Cairoli, Antoinette Buhle Ndweni)
Chapter 4: Introduction to Statistical Modelling (Gianluca Baio)

Part 2: Modelling Tools

Chapter 5: Individual Level Data (Mi Jun Keng, Iryna Schlackow, Eleanor Pullenayegum)
Chapter 6: Missing Data (Andrea Gabrio, Alexina Mason, Baptiste Leurent, Manuel Gomes)
Chapter 7: Introduction to Survival Analysis in HTA (Christopher Jackson, Nick Latimer, Jeroen Jansen, Petros Pechlivanoglou, Gianluca Baio)
Chapter 8: Decision Tree Models (Nathan Green, Eline Krijkamp, Howard Z Thom, Padraig Dixon)
Chapter 9: Cohort Markov Models in Discrete Time (Howard Z Thom, Pedro Saramago, Marta Soares, Eline Krijkamp, Felicity Lamrock)
Chapter 10: Network Meta-Analysis (Howard Z Thom, Nicky J Welton, David M Phillippo, Mathias Harrer)

Part 3: Advanced Modelling Tools

Chapter 11: Continuous Time Multistate Models (Howard Thom, Devin Incerti, Christopher Jackson, Felicity Lamrock, Claire Williams)
Chapter 12: Discrete Event Simulation in R (Koen Degeling, Mark Clements, Erik Koffijberg, James O’ Mahony, Mohsen Sadatsafavi, Petros Pechlivanoglou)
Chapter 13: Population-Adjusted Indirect Comparisons (David M. Phillippo, Jeroen P. Jansen, Antonio Remiro-Azócar, Howard Z Thom)
Chapter 14: R and Shiny in HTA (Rose Hart, Darren Burns, Mark Strong, Andrea Berardi, Dawn Lee)