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Bayesian Cost-Effectiveness Analysis with the R package BCEA

  • Gianluca Baio
  • Andrea Berardi
  • Anna Heath

Part of the Use R! book series (USE R)

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Gianluca Baio, Andrea Berardi, Anna Heath
    Pages 1-22
  3. Gianluca Baio, Andrea Berardi, Anna Heath
    Pages 23-57
  4. Gianluca Baio, Andrea Berardi, Anna Heath
    Pages 59-92
  5. Gianluca Baio, Andrea Berardi, Anna Heath
    Pages 93-152
  6. Gianluca Baio, Andrea Berardi, Anna Heath
    Pages 153-166
  7. Back Matter
    Pages 167-168

About this book

Introduction

The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some relevant theory and introductory concepts are presented using practical examples and two running case studies. The book also describes in detail how to perform health economic evaluations using the R package BCEA (Bayesian Cost-Effectiveness Analysis). BCEA can be used to post-process the results of a Bayesian cost-effectiveness model and perform advanced analyses producing standardised and highly customisable outputs. It presents all the features of the package, including its many functions and their practical application, as well as its user-friendly web interface. The book is a valuable resource for statisticians and practitioners working in the field of health economics wanting to simplify and standardise their workflow, for example in the preparation of dossiers in support of marketing authorisation, or academic and scientific publications.

Keywords

Bayesian modelling Cost-effectiveness Analysis Probabilistic sensitivity analysis Decision-analytic modelling Health economics evaluation Value of Information Health techonology assessment Bayesian Cost-Effectiveness Analysis BCEA

Authors and affiliations

  • Gianluca Baio
    • 1
  • Andrea Berardi
    • 2
  • Anna Heath
    • 3
  1. 1.Department of Statistical ScienceUniversity College LondonLondonUnited Kingdom
  2. 2.Department of StatisticsUniversity of Milano BicoccaMilanoItaly
  3. 3.Department of Statistical ScienceUniversity College LondonLondonUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-55718-2
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-55716-8
  • Online ISBN 978-3-319-55718-2
  • Series Print ISSN 2197-5736
  • Series Online ISSN 2197-5744
  • Buy this book on publisher's site