Individual Participant Data Meta-Analysis

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Individual Participant Data Meta-Analysis: краткое содержание, описание и аннотация

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Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research 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.

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WILEY SERIES IN STATISTICS IN PRACTICE

Advisory Editor, Marian Scott, University of Glasgow, Scotland, UK

Founding Editor, Vic Barnett, Nottingham Trent University, UK

Statistics in Practice is an important international series of texts which provide detailed coverage of statistical concepts, methods, and worked case studies in specific fields of investigation and study.

With sound motivation and many worked practical examples, the books show in down-to-earth terms how to select and use an appropriate range of statistical techniques in a particular practical field within each title's special topic area.

The books provide statistical support for professionals and research workers across a range of employment fields and research environments. Subject areas covered include medicine and pharmaceutics; industry, finance, and commerce; public services; the earth and environmental sciences, and so on.

The books also provide support to students studying statistical courses applied to the above areas. The demand for graduates to be equipped for the work environment has led to such courses becoming increasingly prevalent at universities and colleges.

It is our aim to present judiciously chosen and well-written workbooks to meet everyday practical needs. Feedback of views from readers will be most valuable to monitor the success of this aim.

A complete list of titles in this series appears at the end of the volume.

Human and Biological Sciences

Brown and Prescott · Applied Mixed Models in Medicine

Ellenberg, Fleming, and DeMets · Data Monitoring Committees in Clinical Trials: A Practical Perspective

Lawson, Browne, and Vidal Rodeiro · Disease Mapping With WinBUGS and MLwiN

Lui · Statistical Estimation of Epidemiological Risk

Marubini and Valsecchi · Analysing Survival Data from Clinical Trials and Observation Studies

Parmigiani · Modeling in Medical Decision Making: A Bayesian Approach

Senn · Cross-over Trials in Clinical Research, Second Edition

Senn · Statistical Issues in Drug Development

Spiegelhalter, Abrams, and Myles · Bayesian Approaches to Clinical Trials and Health-Care Evaluation

Turner · New Drug Development: Design, Methodology, and Analysis

Whitehead · Design and Analysis of Sequential Clinical Trials, Revised Second Edition

Whitehead · Meta-Analysis of Controlled Clinical Trials

Zhou, Zhou, Liu, and Ding · Applied Missing Data Analysis in the Health Sciences

Earth and Environmental Sciences

Buck, Cavanagh and Litton · Bayesian Approach to Interpreting Archaeological Data

Cooke · Uncertainty Modeling in Dose Response: Bench Testing Environmental Toxicity

Gibbons, Bhaumik, and Aryal · Statistical Methods for Groundwater Monitoring, Second Edition

Glasbey and Horgan · Image Analysis in the Biological Sciences

Helsel · Nondetects and Data Analysis: Statistics for Censored Environmental Data

Helsel · Statistics for Censored Environmental Data Using Minitab ® and R, Second Edition

McBride · Using Statistical Methods for Water Quality Management: Issues, Problems and Solutions

Ofungwu · Statistical Applications for Environmental Analysis and Risk Assessment

Webster and Oliver · Geostatistics for Environmental Scientists

Industry, Commerce and Finance

Aitken and Taroni · Statistics and the Evaluation of Evidence for Forensic Scientists, Second Edition

Brandimarte · Numerical Methods in Finance and Economics: A MATLAB-Based Introduction, Second Edition

Brandimarte and Zotteri · Introduction to Distribution Logistics

Chan and Wong · Simulation Techniques in Financial Risk Management, Second Edition

Jank · Statistical Methods in eCommerce Research

Jank and Shmueli · Modeling Online Auctions

Lehtonen and Pahkinen · Practical Methods for Design and Analysis of Complex Surveys, Second Edition

Lloyd · Data Driven Business Decisions

Ohser and Mücklich · Statistical Analysis of Microstructures in Materials Science

Rausand · Risk Assessment: Theory, Methods, and Applications

Individual Participant Data Meta‐Analysis

A Handbook for Healthcare Research

Edited by

Richard D. Riley

Keele University

Keele, UK

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