Del 387 - Wiley Series in Probability and Statistics - Applied Probability and Statistics Section

Methods for Meta-Analysis in Medical Research

Inbunden, Engelska, 2000

Av Alexander J. Sutton, Keith R. Abrams, David R Jones, Trevor A. Sheldon, Fujian Song, UK) Sutton, Alexander J. (University of Leicester, UK) Abrams, Keith R. (University of Leicester, UK) Jones, David R (University of Leicester, UK) Sheldon, Trevor A. (University of York, UK) Song, Fujian (University of York, Sutton, Alexander J Sutton, Keith R Abrams, Trevor A Sheldon

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With meta-analysis methods playing a crucial role in health research in recent years, this important and clearly-written book provides a much-needed survey of the field.Meta-analysis provides a framework for combining the results of several clinical trials and drawing inferences about the effectiveness of medical treatments. The move towards evidence-based health care and practice is underpinned by the use of meta-analysis. This book:* Provides a thorough criticism and an up-to-date survey of meta-analysis methods* Emphasises the practical approach, and illustrates the methods by numerous examples* Describes the use of Bayesian methods in meta-analysis* Includes discussion of appropriate software for each analysis* Includes numerous references to more advanced treatment of specialist topics* Refers to software code used in the examples available on the authors' Web sitePractising statisticians, statistically-minded clinicians and health research professionals will benefit greatly from the clear presentation and numerous examples. Medical researchers will grasp the basic principles of meta-analysis, and learn how to apply the various methods.

Produktinformation

Utgivningsdatum2000-10-24
Mått160 x 238 x 25 mm
Vikt652 g
FormatInbunden
SpråkEngelska
SerieWiley Series in Probability and Statistics - Applied Probability and Statistics Section
Antal sidor352
FörlagJohn Wiley & Sons Inc
ISBN9780471490661

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Alex Sutton has published extensively on meta-analysis methodology generally, and on publication bias specifically in recent years, including a major systematic review on the topic of the methodology that has been developed for meta-analysis. He currently has an active interest in the area of partially reported study information, which is currently under-researched. Dr. Sutton is co-author of a textbook on metaanalysis (Methods for Meta Analysis in Medical Research), which was published by Wiley in 2000.

PART A: META-ANALYSIS METHODOLOGY: THE BASICS Introduction: Meta-analysis: Its Development and Uses Defining Outcome Measures used for Combining via Meta-analysis Random Effects Models for Combining Study Estimates Exploring Between Study Heterogeneity Publication Bias Study Quality Sensitivity Analysis Reporting the Results of a Meta-analysis Fixed Effects Methods for Combining Study Estimates PART B: ADVANCED AND SPECIALIZED META-ANALYSIS TOPICS Bayesian Methods in Meta-analysis Meta Regression Meta-analysis of Different Types of Data Incorporating Study Quality into a Meta-analysis Meta-analysis of Multiple and Correlated Outcome Measures Meta-analysis of Epidemiological and other Observational Studies Generalised Synthesis of Evidence -Combining Different Sources of Evidence Meta-analysis of Survival Data Cumulative Meta-analysis Miscellaneous and Developing Areas of Applications in Meta-Analysis Appendix I: Software Used for the Examples in this Book

“Both books can be recommended for graduate training and are useful additions to the library of those interested in the meta-analytic accumulation of literatures on training, vocational learning, and education in the professions.” (Vocations and Learning, 15 December 2010)"This well-written book offers an exhaustive criticism and up-to-date references, illustrates effectively with real life examples and data…" (Journal of Statistical Computation & Simulation, July 2004) "this is an excellent book..." (Short Book Reviews, April 2001)"...recommended for mathematically skilled readers interested in getting an overview of the various methods and the existing literature..." (Statistics in Medicine, 15 October 2003)