|Introduction to Meta-Analysis|
by Michael Borenstein (Author), Larry V. Hedges (Author), Julian P. T. Higgins (Author), Hannah R. Rothstein (Author)
This book provides a clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. Meta-analysis has become a critically important tool in fields as diverse as medicine, pharmacology, epidemiology, education, psychology, business, and ecology. Introduction to Meta-Analysis: Outlines the role of meta-analysis in the research process Shows how to compute effects sizes and treatment effects Explains the fixed-effect and random-effects...
|The Handbook of Research Synthesis and Meta-Analysis|
by Harris Cooper (Editor), Larry V. Hedges (Editor), Jeffrey C. Valentine (Editor)
Praise for the first edition:
“The Handbook is a comprehensive treatment of literature synthesis and provides practical advice for anyone deep in the throes of, just teetering on the brink of, or attempting to decipher a meta-analysis. Given the expanding application and importance of literature synthesis, understanding both its strengths and weaknesses is essential for its practitioners and consumers. This volume is a good beginning for those who wish to gain...
|Network Meta-Analysis for Decision-Making (Statistics in Practice)|
by Sofia Dias (Author), A. E. Ades (Author), Nicky J. Welton (Author), Jeroen P. Jansen (Author), Alexander J. Sutton (Author)
A practical guide to network meta-analysis with examples and code
In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when...
|Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan|
by John Kruschke (Author)
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular,...