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Mission

R for Health Technology Assessment (HTA) is an academic consortium whose main objective is to explore the use of R for cost-effectiveness analysis (CEA) as an alternative to less efficient, generalisable and powerful software such as spreadsheets. R is a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques. We advocate the use of proper statistical software, notably R, to be used in the whole process of health economic evaluation.

General topics of interest include a wide range of technical aspects, e.g. the discussion of the many available R add-on packages, as well as ways to help users get the most out of R for CEA. Presentations and public discussions are used to address the computational and transparency advantages of R over Excel for CEA and for easing collaboration. Our members have diverse experience in government (including NICE in the UK), academia, and industry.

Events

Our events, including the annual workshop, short courses and hackathons

R for HTA annual workshop

Next edition: 28 June - 02 July 2024. Check for updates!

Training events

Here’s a list of all the training events that are organised by members of our consortium

Hackathons

Come and play with R!

Online R resources

Relevant R packages and tools for statistical analysis and economic evaluation

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BCEA

Bayesian Cost-Effectiveness Analysis

SAVI

Sheffield Accelerated Value of Information

survHE

Survival analysis in health economic evaluation

flexsurv

Flexible Parametric Survival and Multi-State Models

hesim

Discrete and continuous time Markov/semi-Markov models

heemod

Discrete-time Markov modelling

MAIC

Facilitates performing matching-adjusted indirect comparison (MAIC) analysis for a disconnected treatment network

gemtcPlus

Convinience functions for perfoming Bayesian NMA using the gemtc package

rpsftmPlus

Convenience functions for working with the rpsftm package and general analysis of trials affected by treatment switching

msm

Continuous-time Markov models fit to panel data and hidden Markov models

mstate

Continuous-time Markov/semi-Markov models

missingHE

Health economic evaluations with missing data using a set of pre-defined Bayesian models

EVSI

Calculation and presentation of the Expected Value of Sample Information

aldvmm

Adjusted Limited Dependent Variable Mixture Models of Health-Related Quality of Life in R

Standalone R code

Various scripts/code

Members of the consortium

Co-director

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Howard Thom

Lecturer in Health Economics

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Felicity Lamrock

Senior Lecturer in Data Analytics

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Robert Smith

Director & Health Economist

Scientific committee

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Gianluca Baio

Professor of Statistics and Health Economics

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Raquel Aguiar-Ibanez

Senior Principal Scientist

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Fernando Alarid-Escudero

Assistant Professor

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Padraig Dixon

Research Fellow

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Nathan Green

Research Fellow

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Anthony Hatswell

Director and Analyst

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Anna Heath

Assistant Professor

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Devin Incerti

Principal Data Scientist

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Dawn Lee

Associate Professor of Health Economics and Health Policy

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James O'Mahony

Research Assistant Professor in Public Health & Primary Care

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Pedro Saramago

Research Fellow

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Lea Trela-Larsen

Senior Statistician

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Nicky Welton

Professor in Statistical and Health Economic Modelling

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Claire Williams

Senior Researcher in Health Economics

Relevant institutions

UCL
Bristol
CHE
Trinity College Dublin
National Centre for Pharmacoeconomics
Center for Research and Teaching in Economics
Sickkids Toronto

Contact