By Michael Borenstein, Larry V. Hedges, Julian P. T. Higgins, Hannah R. Rothstein
This booklet offers a transparent and thorough advent to meta-analysis, the method of synthesizing info from a chain of separate reports. Meta-analysis has develop into a significantly very important instrument in fields as various as medication, pharmacology, epidemiology, schooling, psychology, enterprise, and ecology. advent to Meta-Analysis :
- Outlines the function of meta-analysis within the study procedure
- Shows find out how to compute results sizes and remedy results
- Explains the fixed-effect and random-effects types for synthesizing info
- Demonstrates how you can determine and interpret edition in impact dimension throughout experiences
- Clarifies innovations utilizing textual content and figures, via formulation and examples
- Explains the best way to keep away from universal blunders in meta-analysis
- Discusses controversies in meta-analysis
- Features a website with extra fabric and workouts
an exceptional blend of lucid prose and informative snap shots, written through 4 of the world’s best specialists on all features of meta-analysis. Borenstein, Hedges, Higgins, and Rothstein supply a fresh departure from cookbook methods with their transparent factors of the what and why of meta-analysis. The e-book is perfect as a direction textbook or for self-study. My scholars, who used pre-publication models of a few of the chapters, raved in regards to the readability of the reasons and examples. David Rindskopf, exotic Professor of academic Psychology, urban college of latest York, Graduate tuition and college heart, & Editor of the magazine of academic and Behavioral facts .
The technique taken by way of creation to Meta-analysis is meant to be essentially conceptual, and it truly is amazingly profitable at attaining that objective. The reader can with ease bypass the formulation and nonetheless comprehend their program and underlying motivation. For the extra statistically refined reader, the suitable formulation and labored examples offer an excellent functional advisor to appearing a meta-analysis. The e-book presents an eclectic mixture of examples from schooling, social technological know-how, biomedical reviews, or even ecology. For an individual contemplating major a direction in meta-analysis, or pursuing self-directed examine, creation to Meta-analysis will be a transparent first selection. Jesse A. Berlin, ScDВ
creation to Meta-Analysis is a superb source for rookies and specialists alike. The publication offers a transparent and complete presentation of all simple and so much complex ways to meta-analysis. This booklet could be referenced for many years. Michael A. McDaniel, Professor of Human assets and Organizational habit, Virginia Commonwealth collage
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Extra info for Introduction to Meta-Analysis
Sample text
By pooling the two estimates of the standard deviation, we obtain a more accurate estimate of their common value. The sample estimate of the standardized mean difference is often called Cohen’s d in research synthesis. Some confusion about the terminology has resulted from the fact that the index , originally proposed by Cohen as a population parameter for describing the size of effects for statistical power analysis is also sometimes called d. In this volume we use the symbol to denote the effect size parameter and d for the sample estimate of that parameter.
2 Fictional data for a 2 Â 2 table. Treated Control Dead Alive N 5 10 95 90 100 100 Introduction to Meta-Analysis M. Borenstein, L. V. Hedges, J. P. T. Higgins, H. R. Rothstein Ó 2009, John Wiley & Sons, Ltd 34 Effect Size and Precision From these data we might compute a risk ratio, an odds ratio, and/or a risk difference. RISK RATIO The risk ratio is simply the ratio of two risks. 50. This index has the advantage of being intuitive, in the sense that the meaning of a ratio is clear. For risk ratios, computations are carried out on a log scale.
To borrow a phrase from Abelson, it involves doing arithmetic with words. And, when the words are based on p-values the words are the wrong words. By contrast, in a meta-analysis we introduce two fundamental changes. First, we work directly with the effect size from each study rather than the p-value. Second, we include all of the effects in a single statistical synthesis. This is critically important for the goal of computing (and testing) a summary effect. Meta-analysis also allows us to assess the dispersion of effects, and distinguish between real dispersion and spurious dispersion.