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Doing Meta-Analysis with R
Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the ...
Cultures of Computer Game Concerns
Biographical note: Estrid Sörensen is a Professor of Cultural Psychology and Anthropology of Knowledge at the Ruhr-University Bochum. She does research within Science & Technology Studies.
Publication Bias in Meta-Analysis
Publication bias is the tendency to decide to publish a study based on the results of the study, rather than on the basis of its theoretical or methodological quality. It can arise from selective publication of favorable results, or of statistically significant results. This threatens the validity of conclusions drawn from reviews of published scientific research. Meta-analysis is now used in numerous scientific disciplines, summarizing quantitative evidence from multiple studies. If the literature being synthesised has been affected by publication bias, this in turn biases the meta-analytic results, potentially producing overstated conclusions. Publication Bias in Meta-Analysis examines the...
Diseases of the Pancreas
"This clearly laid out and easily readable encyclopedia is aimed particularly at general practitioners and students in their clinical years, as well as at specialists who desire a more in-depth knowledge of the pancreas, such as internists, gastroenterologists, surgeons, radiologists, oncologists, pathologists and pediatricians. But others will also find this to be a comprehensive reference book on the subject."--BOOK JACKET.
Network Meta-Analysis for Decision-Making
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 there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question "for this pre-identified population of patients, which treatment is 'best'?" A co...
Bats
This extravagantly illustrated handbook features the work of famed nature photographer Merlin D. Tuttle and in-depth profiles of megabats and microbats.
Meta-Analysis
Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are b...
Foundations of Agnostic Statistics
Provides an introduction to modern statistical theory for social and health scientists while invoking minimal modeling assumptions.
