rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Network meta-analysis for decision making
  name:
    name part: Dias, Sofia
    name part: 1977-
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: nju
    date issued: 2018
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question "for this pre-identified population of patients, which treatment is 'best''" A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader.-Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised.-Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal.-Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons.-Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical indust…
  table of contents: 1. Introduction to evidence synthesis -- 2. The core model -- 3. Model fit, model comparison and outlier detection -- 4. Generalised linear models -- 5. Network meta-analysis within cost-effectiveness analysis -- 6. Adverse events and other sparse outcome data -- 7. Checking for inconsistency -- 8. Meta-regression for relative treatment effects -- 9. Bias adjustment methods -- 10. Network meta-analysis of survival outcomes -- 11. Multiple outcomes -- 12. Validity of network meta-analysis -- Solutions to exercises -- Appendices -- References -- Index.
  note: by Sofia Dias, University of Bristol, Bristol, UK [and four others].
  note: Includes bibliographical references and index.
  subject:
    topic: Meta-analysis
  subject:
    topic: Mathematical analysis
  subject:
    topic: Cost effectiveness
  subject:
    topic: Network Meta-Analysis
  subject:
    topic: Cost-Benefit Analysis
  classification: R853.M48 N47 2018
  classification: 610.72/7
  classification: WA 950
  related item:
    title info:
      title: Wiley Series in Statistics in Practice
  related item:
    title info:
      title: Network meta-analysis for decision making
    origin info:
      publisher: Hoboken, NJ : Wiley, 2018
    identifier: (DLC) 2017036441
  identifier: 9781118951712
  identifier: 1118951719
  identifier: 9781118951729
  identifier: 1118951727
  identifier: 9781118951651
  identifier: 1118951654
  identifier: 9781118647509
  identifier: 1118647505
  identifier: 2017048849
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 171011
    record change date: 20260214212006.0
    record identifier: in00004682888
    language of cataloging:
      language term: eng