Titlebook: Meta-Research; Methods and Protocol Evangelos Evangelou,Areti Angeliki Veroniki Book 2022 Springer Science+Business Media, LLC, part of Spr

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Assessing Heterogeneity in Random-Effects Meta-analysis, not only due to random sampling error but also due to inherent differences in the way studies have been designed and conducted. In this chapter, we consider methods to estimate the heterogeneity variance parameter in a random-effects model, consider in more detail what this parameter represents and

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Systematic Versus Rapid Versus Scoping Reviews,ative approaches for knowledge synthesis: rapid reviews and scoping reviews. In doing so, the intention is to provide readers with guidance in determining whether a rapid or scoping review may be more appropriate for addressing the research question(s) and objective(s) of the review team and knowled

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Umbrella Reviews: What They Are and Why We Need Them,lable information should be critically assessed. Here, we focus on umbrella reviews, an approach that systematically collects and evaluates information from multiple systematic reviews and meta-analyses. To facilitate the design and the conduct of such a study, we provide a step-by-step guide on how

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Meta-Analysis of Proportions,es are conducted in various fields of science, including medicine, ecology, psychology, or social sciences. In this chapter, we illustrate meta-analysis methods to pool single proportions and to compare proportions from two groups. We introduce classic approaches based on the inverse variance method

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Network Meta-Analysis, available interventions. In contrast to pairwise meta-analysis, which allows for the comparison of one intervention to another based on head-to-head data from randomized trials, network meta-analysis (NMA) facilitates simultaneous comparison of the efficacy or?safety of multiple interventions that

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Contrast-Based and Arm-Based Models for Network Meta-Analysis,ose used for pairwise meta-analysis. Two types of models are available to undertake a network meta-analysis: contrast-based and arm-based models. Contrast-based models have been used in most published network meta-analyses. Arm-based models offer greater flexibility and handle treatments symmetrical