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Handbook of Meta-Analysis

Edited by: Christopher H. Schmid , Theo Stijnen , Ian R. White

Print publication date:  September  2020
Online publication date:  September  2020

Print ISBN: 9781498703987
eBook ISBN: 9781315119403
Adobe ISBN:

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Book description

Meta-analysis is the application of statistics to combine results from multiple studies and draw appropriate inferences. Its use and importance have exploded over the last 25 years as the need for a robust evidence base has become clear in many scientific areas, including medicine and health, social sciences, education, psychology, ecology, and economics.

Recent years have seen an explosion of methods for handling complexities in meta-analysis, including explained and unexplained heterogeneity between studies, publication bias, and sparse data. At the same time, meta-analysis has been extended beyond simple two-group comparisons of continuous and binary outcomes to comparing and ranking the outcomes from multiple groups, to complex observational studies, to assessing heterogeneity of effects, and to survival and multivariate outcomes. Many of these methods are statistically complex and are tailored to specific types of data.

Key features

  • Rigorous coverage of the full range of current statistical methodology used in meta-analysis
  • Comprehensive, coherent, and unified overview of the statistical foundations behind meta-analysis
  • Detailed description of the primary methods for both univariate and multivariate data
  • Computer code to reproduce examples in chapters
  • Thorough review of the literature with thousands of references
  • Applications to specific types of biomedical and social science data

This book is for a broad audience of graduate students, researchers, and practitioners interested in the theory and application of statistical methods for meta-analysis. It is written at the level of graduate courses in statistics, but will be of interest to and readable for quantitative scientists from a range of disciplines. The book can be used as a graduate level textbook, as a general reference for methods, or as an introduction to specialized topics using state-of-the art methods.

Table of contents

Prelims Download PDF
Chapter  1:  Introduction to Systematic Review and Meta-Analysis Download PDF
Chapter  2:  General Themes in Meta-Analysis Download PDF
Chapter  3:  Choice of Effect Measure and Issues in Extracting Outcome Data Download PDF
Chapter  4:  Analysis of Univariate Study-Level Summary Data Using Normal Models Download PDF
Chapter  5:  Exact Likelihood Methods for Group-Based Summaries Download PDF
Chapter  6:  Bayesian Methods for Meta-Analysis Download PDF
Chapter  7:  Meta-Regression Download PDF
Chapter  8:  Individual Participant Data Meta-Analysis Download PDF
Chapter  9:  Multivariate Meta-Analysis Download PDF
Chapter  10:  Network Meta-Analysis Download PDF
Chapter  11:  Model Checking in Meta-Analysis Download PDF
Chapter  12:  Handling Internal and External Biases:  Download PDF
Chapter  13:  Publication and Outcome Reporting Bias Download PDF
Chapter  14:  Control Risk Regression Download PDF
Chapter  15:  Multivariate Meta-Analysis of Survival Proportions Download PDF
Chapter  16:  Meta-Analysis of Correlations, Correlation Matrices, and Their Functions Download PDF
Chapter  17:  The Meta-Analysis of Genetic Studies Download PDF
Chapter  18:  Meta-Analysis of Dose-Response Relationships Download PDF
Chapter  19:  Meta-Analysis of Diagnostic Tests Download PDF
Chapter  20:  Meta-Analytic Approach to Evaluation of Surrogate Endpoints Download PDF
Chapter  21:  Meta-Analysis of Epidemiological Data, with a Focus on Individual Participant Data Download PDF
Chapter  22:  Meta-Analysis of Prediction Models Download PDF
Chapter  23:  Using Meta-Analysis to Plan Further Research Download PDF
Index Download PDF
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