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Informationen zum Autor Anne Whitehead is Senior Lecturer in Modern and Contemporary Literature at Newcastle University, UK. She is the author of many books. Klappentext Over the last twenty years there has been a dramatic upsurge in the application of meta-analysis to medical research. This has mainly been due to greater emphasis on evidence-based medicine and the need for reliable summaries of the vast and expanding volume of clinical research. At the same time there have been great strides in the development and refinement of the associated statistical methodology. This book describes the planning, conduct and reporting of a meta-analysis as applied to a series of randomized controlled clinical trials.* The various approaches are presented within a general unified framework.* Meta-analysis techniques are described in detail, from their theoretical development through to practical implementation.* Each topic discussed is supported by detailed worked examples.* A comparison of fixed and random effects approaches is included, as well as a discussion of Bayesian methods and cumulative meta-analysis.* Fully documented programs using standard statistical procedures in SAS are available on the Web.Ideally suited for practising statisticians and statistically-minded medical professionals, the book will also be of use to graduate students of medical statistics. The book is a self-contained and comprehensive account of the subject and an essential purchase for anyone involved in clinical trials. Zusammenfassung Over the last twenty years there has been a dramatic upsurge in the application of meta-analysis to medical research. This has mainly been due to greater emphasis on evidence-based medicine and the need for reliable summaries of the vast and expanding volume of clinical research. At the same time there have been great strides in the development and refinement of the associated statistical methodology. This book describes the planning, conduct and reporting of a meta-analysis as applied to a series of randomized controlled clinical trials.* The various approaches are presented within a general unified framework.* Meta-analysis techniques are described in detail, from their theoretical development through to practical implementation.* Each topic discussed is supported by detailed worked examples.* A comparison of fixed and random effects approaches is included, as well as a discussion of Bayesian methods and cumulative meta-analysis.* Fully documented programs using standard statistical procedures in SAS are available on the Web.Ideally suited for practising statisticians and statistically-minded medical professionals, the book will also be of use to graduate students of medical statistics. The book is a self-contained and comprehensive account of the subject and an essential purchase for anyone involved in clinical trials. Inhaltsverzeichnis Introduction Protocol development Estimating the treatment difference in an individual trial Combining estimates of a treatment difference across trials Meta-analysis using individual patient data Dealing with heterogeneity Presentation and interpretation of results Selection bias Dealing with non-standard datasets Inclusion of trials with different study designs A Bayesian approach to meta-analysis Sequential methods for meta-analysis Appendix Methods of estimation and hypothesis testing...
Sommario
Introduction
Protocol development
Estimating the treatment difference in an individual trial
Combining estimates of a treatment difference across trials
Meta-analysis using individual patient data
Dealing with heterogeneity
Presentation and interpretation of results
Selection bias
Dealing with non-standard datasets
Inclusion of trials with different study designs
A Bayesian approach to meta-analysis
Sequential methods for meta-analysis
Appendix Methods of estimation and hypothesis testing
Relazione
"...highly recommended as essential reading for medical statisticians..." (Short Book Reviews, April 2003)
"...comprehensive and well illustrated contribution to the subject...useful for graduate students of medical statistics..." (Statistics in Medicine, Vol 23(3), 15 February 2004)
