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Modern meta-analyses do more than combine the effect sizes of a series of similar studies. Meta-analyses are currently increasingly applied for any analysis beyond the primary analysis of studies, and for the analysis of big data. This 26-chapter book was written for nonmathematical professionals of medical and health care, in the first place, but, in addition, for anyone involved in any field involving scientific research. The authors have published over twenty innovative meta-analyses from the turn of the century till now. This edition will review the current state of the art, and will use for that purpose the methodological aspects of the authors' own publications, in addition to other relevant methodological issues from the literature.

Are there alternative works in the field? Yes, there are, particularly in the field of psychology. Psychologists have invented meta-analyses in 1970, and have continuously updated methodologies. Although very interesting, their work, just like the whole discipline of psychology, is rather explorative in nature, and so is their focus to meta-analysis. Then, there is the field of epidemiologists. Many of them are from the school of angry young men, who publish shocking news all the time, and JAMA and other publishers are happy to publish it. The reality is, of course, that things are usually not as bad as they seem. Finally, some textbooks, written by professional statisticians, tend to use software programs with miserable menu programs and requiring lots of syntax to be learnt. This is prohibitive to clinical and other health professionals.

The current edition is the first textbook in the field of meta-analysis entirely written by two clinical scientists, and it consists of many data examples and step by step analyses, mostly from the authors' own clinical research. 

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Modern meta-analyses do more than combine the effect sizes of a series of similar studies. Meta-analyses are currently increasingly applied for any analysis beyond the primary analysis of studies, and for the analysis of big data. This 26-chapter book was written for nonmathematical professionals of medical and health care, in the first place, but, in addition, for anyone involved in any field involving scientific research. The authors have published over twenty innovative meta-analyses from the turn of the century till now. This edition will review the current state of the art, and will use for that purpose the methodological aspects of the authors' own publications, in addition to other relevant methodological issues from the literature.

Are there alternative works in the field? Yes, there are, particularly in the field of psychology. Psychologists have invented meta-analyses in 1970, and have continuously updated methodologies. Although very interesting, their work, just like the whole discipline of psychology, is rather explorative in nature, and so is their focus to meta-analysis. Then, there is the field of epidemiologists. Many of them are from the school of angry young men, who publish shocking news all the time, and JAMA and other publishers are happy to publish it. The reality is, of course, that things are usually not as bad as they seem. Finally, some textbooks, written by professional statisticians, tend to use software programs with miserable menu programs and requiring lots of syntax to be learnt. This is prohibitive to clinical and other health professionals.

The current edition is the first textbook in the field of meta-analysis entirely written by two clinical scientists, and it consists of many data examples and step by step analyses, mostly from the authors' own clinical research. 

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Preface

Chapter 1.                               

Meta-Analysis in a Nutshell 

Chapter 2.                               

Mathematical Framework

Chapter 3.                               

Meta-Analysis and the Scientific Method

Chapter 4.                               

Meta-Analysis and Random Effects Analysis

Chapter 5.                               

Meta-Analysis Software Programs

Chapter 6.                               
Meta-Analysis of Randomized Controlled Trials

Chapter 7.                               

Meta-Analysis of Observational plus Randomized Studies  

Chapter 8.                               
Meta-Analysis of Observational Studies   

Chapter 9.                               

Meta-Regression

Chapter 10.                               

Meta-Analysis of Diagnostic Studies       

Chapter 11.                               

Meta-Meta-Analyses 

Chapter 12.                               

Network Meta-Analysis

Chapter 13.                               

Random Intercepts Meta-Analysis
Chapter 14.                               

Probit Regression 

Chapter 15.                               

Meta-Analysis with General Loglinear Models

  Chapter 16.                                 

 Meta-Analysis with Variance Components 

 Chapter 17.                               
 Ensembled Correlation Coefficients

Chapter 18.                               

Ensembled Accuracies

Chapter 19.                               

Meta-Analyses with Multivariate Assessments

Chapter 20.                               <

 Transforming Odds Ratios into Correlation Coefficients 

 Chapter 21.                               

 Meta-Analyses with Direct and Indirect Comparisons 

 Chapter 22.                               

 Contrast Coefficients Meta-Analysis 

 Chapter 23.                               

 Meta-Analysis with Evolutionary Operations 
 Chapter 24.                               

Meta-Analysis with Heterogeneity Rather than Homogeneity of Studies as Null-Hypothesis

Chapter 25.                               

Meta-Analytic Thinking and Other Spin-Offs of Meta-Analysis

Chapter 26.                               
< Novel Developments<

 Index 

< 

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