By Julia Koricheva, Jessica Gurevitch, Kerrie Mengersen
Meta-analysis is a robust statistical method for synthesizing learn proof throughout autonomous experiences. this is often the 1st finished guide of meta-analysis written in particular for ecologists and evolutionary biologists, and it offers a useful creation for novices in addition to an up to date consultant for skilled meta-analysts.
The chapters, written by means of well known specialists, stroll readers via each step of meta-analysis, from challenge formula to the presentation of the implications. The guide identifies either the benefits of utilizing meta-analysis for examine synthesis and the aptitude pitfalls and barriers of meta-analysis (including whilst it may no longer be used). various techniques to accomplishing a meta-analysis are defined, and comprise second and least-square, greatest chance, and Bayesian techniques, all illustrated utilizing labored examples in accordance with genuine organic datasets. This exceptional source is uniquely adapted to the organic sciences, and may offer a useful textual content for practitioners from graduate scholars and senior scientists to policymakers in conservation and environmental management.
- Walks you thru each step of undertaking a meta-analysis in ecology and evolutionary biology, from challenge formula to consequence presentation
- Brings jointly specialists from a huge variety of fields
- Shows the way to steer clear of, reduce, or get to the bottom of pitfalls resembling lacking information, book bias, various info caliber, nonindependence of observations, and phylogenetic dependencies between species
- Helps you decide the perfect software program
- Draws on quite a few examples in line with actual organic datasets
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Extra resources for Handbook of Meta-analysis in Ecology and Evolution
2009, 215–45). They provide very simple, fully worked examples of how to calculate effect sizes and variance in each case. These should help you to decide on the best protocol for your meta-analysis. One complicating issue in ecological and evolutionary meta-analyses is that there might be nonindependence between studies due to a shared phylogeny history. This can occur when studies of the same species or closely related species produce more similar results (effect sizes) than those from distantly related taxa.
Specifically, if treatment effects are measured repeatedly over time, you need criteria to determine which comparisons you will use. Likewise, if there is a single control and several treatments varying in magnitude, will you extract all treatment-control comparisons, or only the one between the control and the most extreme treatment? The statistical issues surrounding nonindependence of effect sizes are dealt with in Chapters 16 and 17. If you want to keep life simple, the easiest solution is to design a protocol that only extracts one effect size per study.
Your protocol). In some cases this could lead to difficulties with reviewers unfamiliar with systematic reviews because such descriptions may, in their eyes, take up too much space in the Methods section. Again, a simple solution is to be concise in the main text and use an electronic appendix to publish your protocol in its entirety. Finally, while it can be useful to consult published meta-analyses to gain a feel for how to present your results, you should remember that meta-analysis is still a relatively new technique in ecology and 24 Chapter 2 evolutionary biology.