Individual participant data meta-analysis : a handbook for healthcare research
Individual participant data meta-analysis : a handbook for healthcare research
- Hoboken, NJ ; Chichester : Wiley, 2021.
- 550 p. : ill. ; 27 cm.
- Wiley series in statistics in practice .
Includes bibliographical references and index.
Rationale for Embarking on an IPD Meta-analysis Project / Jayne F. Tierney, Richard D. Riley, Catrin Tudur Smith, Mike Clarke, and Lesley A. Stewart -- Planning and Initiating an IPD Meta-analysis Project / Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney -- Running an IPD Meta-analysis Project : From Developing the Protocol to Preparing Data for Metaanalysis / Jayne F. Tierney, Richard D. Riley, Larysa H.M. Rydzewska, and Lesley A. Stewart -- The Two-stage Approach to IPD Meta-analysis / Richard D. Riley, Thomas P.A. Debray, Tim P. Morris, and Dan Jackson -- The One-stage Approach to IPD Meta-analysis / Richard D. Riley and Thomas P.A. Debray -- Using IPD Meta-analysis to Examine Interactions between Treatment Effect and Participant-level Covariates / Richard D. Riley and David J. Fisher -- One-stage versus Two-stage Approach to IPD Meta-analysis : Differences and Recommendations / Richard D. Riley, Danielle L. Burke, and Tim Morris -- Examining the Potential for Bias in IPD Meta-analysis Results / Richard D. Riley, Jayne F. Tierney, and Lesley A. Stewart -- Reporting and Dissemination of IPD Meta-analyses / Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney -- A Tool for the Critical Appraisal of IPD Meta-analysis Projects (CheckMAP) / Jayne F. Tierney, Lesley A. Stewart, Claire L. Vale, and Richard D. Riley -- Power Calculations for Planning an IPD Meta-analysis / Richard D. Riley and Joie Ensor -- Multivariate Meta-analysis Using IPD / Richard D. Riley, Dan Jackson, and Ian R. White -- Network Meta-analysis Using IPD / Richard D. Riley, David M. Phillippo, and Sofia Dias -- IPD Meta-analysis for Test Accuracy Research / Richard D. Riley, Brooke Levis, and Yemisi Takwoingi -- IPD Meta-analysis for Prognostic Factor Research / Richard D. Riley, Karel G.M. Moons, and Thomas P.A. Debray -- IPD Meta-analysis for Clinical Prediction Model Research / Richard D. Riley, Kym I.E. Snell, Laure Wynants, Valentijn M.T. de Jong, Karel G.M. Moons, and Thomas P.A. Debray -- Dealing with Missing Data in an IPD Meta-analysis / Thomas Debray, Kym I.E. Snell, Matteo Quartagno, Shahab Jolani, Karel G.M. Moons, and Richard D. Riley.
Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points.
Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data.
Intended for a broad audience, the book will enable the reader to:
Understand the advantages of the IPD approach and decide when it is needed over a conventional systematic review
Recognise the scope, resources and challenges of IPD meta-analysis projects
Appreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators
Understand how to obtain, check, manage and harmonise IPD from multiple studies
Examine risk of bias (quality) of IPD and minimise potential biases throughout the project
Understand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them
Clearly report and disseminate IPD meta-analyses to inform policy, practice and future research
Critically appraise existing IPD meta-analysis projects
Address specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models
Detailed examples and case studies are provided throughout.
9781119333722
Meta-Analysis as Topic
Research
Data Interpretation, Statistical
Models, Statistical
Randomized Controlled Trials as Topic
WA 950
Includes bibliographical references and index.
Rationale for Embarking on an IPD Meta-analysis Project / Jayne F. Tierney, Richard D. Riley, Catrin Tudur Smith, Mike Clarke, and Lesley A. Stewart -- Planning and Initiating an IPD Meta-analysis Project / Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney -- Running an IPD Meta-analysis Project : From Developing the Protocol to Preparing Data for Metaanalysis / Jayne F. Tierney, Richard D. Riley, Larysa H.M. Rydzewska, and Lesley A. Stewart -- The Two-stage Approach to IPD Meta-analysis / Richard D. Riley, Thomas P.A. Debray, Tim P. Morris, and Dan Jackson -- The One-stage Approach to IPD Meta-analysis / Richard D. Riley and Thomas P.A. Debray -- Using IPD Meta-analysis to Examine Interactions between Treatment Effect and Participant-level Covariates / Richard D. Riley and David J. Fisher -- One-stage versus Two-stage Approach to IPD Meta-analysis : Differences and Recommendations / Richard D. Riley, Danielle L. Burke, and Tim Morris -- Examining the Potential for Bias in IPD Meta-analysis Results / Richard D. Riley, Jayne F. Tierney, and Lesley A. Stewart -- Reporting and Dissemination of IPD Meta-analyses / Lesley A. Stewart, Richard D. Riley, and Jayne F. Tierney -- A Tool for the Critical Appraisal of IPD Meta-analysis Projects (CheckMAP) / Jayne F. Tierney, Lesley A. Stewart, Claire L. Vale, and Richard D. Riley -- Power Calculations for Planning an IPD Meta-analysis / Richard D. Riley and Joie Ensor -- Multivariate Meta-analysis Using IPD / Richard D. Riley, Dan Jackson, and Ian R. White -- Network Meta-analysis Using IPD / Richard D. Riley, David M. Phillippo, and Sofia Dias -- IPD Meta-analysis for Test Accuracy Research / Richard D. Riley, Brooke Levis, and Yemisi Takwoingi -- IPD Meta-analysis for Prognostic Factor Research / Richard D. Riley, Karel G.M. Moons, and Thomas P.A. Debray -- IPD Meta-analysis for Clinical Prediction Model Research / Richard D. Riley, Kym I.E. Snell, Laure Wynants, Valentijn M.T. de Jong, Karel G.M. Moons, and Thomas P.A. Debray -- Dealing with Missing Data in an IPD Meta-analysis / Thomas Debray, Kym I.E. Snell, Matteo Quartagno, Shahab Jolani, Karel G.M. Moons, and Richard D. Riley.
Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points.
Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data.
Intended for a broad audience, the book will enable the reader to:
Understand the advantages of the IPD approach and decide when it is needed over a conventional systematic review
Recognise the scope, resources and challenges of IPD meta-analysis projects
Appreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators
Understand how to obtain, check, manage and harmonise IPD from multiple studies
Examine risk of bias (quality) of IPD and minimise potential biases throughout the project
Understand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them
Clearly report and disseminate IPD meta-analyses to inform policy, practice and future research
Critically appraise existing IPD meta-analysis projects
Address specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models
Detailed examples and case studies are provided throughout.
9781119333722
Meta-Analysis as Topic
Research
Data Interpretation, Statistical
Models, Statistical
Randomized Controlled Trials as Topic
WA 950
London Health Libraries Consortium Privacy notice and Membership terms and conditions