Descargar Meta-Analysis with R (Use R!) de Guido Schwarzer,James R. Carpenter,Gerta Rücker PDF ePub
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Meta-Analysis with R (Use R!) de Guido Schwarzer,James R. Carpenter,Gerta Rücker
Descripción - Críticas “A special feature of the book is the focus on comprehensively described examples. For all these examples, the datasets are provided on the book-related website, which allows readers to reproduce and check the R code while working on the book. … it can be warmly recommended to all practical researchers who are involved in performing metaanalysis in R as well as to statisticians who seek a book that gives an overview on metaanalytic methods and their implementations in R.” (Annika Hoyer, Biometrical Journal, Vol. 59 (1), 2017)“In Meta-Analysis with R, Schwarzer, Carptenter, and Rücker present the tools and techniques for doing meta-analyses in R. … The collection of working examples throughout the book is its best feature. Fully worked code examples are provided for almost every problem. … The book is a great introduction to performing meta-analysis in R.” (James P. Howard II, Journal of Statistical Software, Vol. 70, April, 2016)“The book concludes with an appendix containing information on how to install R, how to import data (either from text files or from RevMan5) and an overview of R packages for meta analysis. The style of the book, numerous example and references adjacent to each chapter make it suitable (and very useful) to both undergraduates and postgraduates with either a computing or biological background.” (Irina Ioana Mohorianu, zbMATH 1333.92002, 2016) Reseña del editor This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies. Contraportada This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies. Biografía del autor Guido Schwarzer is a senior statistician and head of IT at the Institute for Medical Biometry and Statistics at the Medical Center - University of Freiburg, Germany. He is an established researcher in the area of meta-analysis and lead statistician of several Cochrane reviews. His special interests are in small-study effects in meta-analysis and statistical computing. Guido Schwarzer is an author of the R packages meta, metasens, and netmeta.James Carpenter studied mathematics at Warwick University and statistics at Oxford University. His principal interests are coping with missing data in complex hierarchical models, sensitivity analysis and meta-analysis, with applications to medical and social data. The collaboration that led to this book began during a sabbatical at Freiburg in 2005–6. James Carpenter is Professor of Medical Statistics at the London School of Hygiene and Tropical Medicine, and Programme Leader in Methodology at the MRC Clinical Trials Unit, London. Gerta Rücker is a mathematician, working at the Institute for Medical Biometry and Statistics at the Medical Center - University of Freiburg, Germany. After having published in chemical graph theory for a number of years, she started working in biostatistics, particularly meta-analysis. Her principal interests are small-study effects and heterogeneity in meta-analysis, meta-analysis of diagnostic accuracy studies and application of graph theory in network meta-analysis. She has published a large number of methodological research papers, co-authored a number of Cochrane reviews and is an author of the R package netmeta.
Detalles del Libro
- Name: Meta-Analysis with R (Use R!)
- Autor: Guido Schwarzer,James R. Carpenter,Gerta Rücker
- Categoria: Libros,Libros universitarios y de estudios superiores,Medicina y ciencias de la salud
- Tamaño del archivo: 15 MB
- Tipos de archivo: PDF Document
- Idioma: Español
- Archivos de estado: AVAILABLE
Descargar Meta-Analysis with R (Use R!) de Guido Schwarzer,James R. Carpenter,Gerta Rücker libros ebooks
Descargar gratis Meta-analysis with r (use r!) ~ Aquí puede descargar el libro Meta-analysis with r (use r!) en formato PDF o EPUB. A continuación, puede leer el libro Meta-analysis with r (use r!) en su ordenador o teléfono - en cualquier momento conveniente para usted.
Meta-Analysis with R (Use R!) (English Edition) eBook ~ This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis.
Meta-Analysis with R / Guido Schwarzer / Springer ~ This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key
(PDF) Meta-Analysis with R - ResearchGate ~ In this chapter we describe the two main methods of meta-analysis, fixed effect model and random effects model, and how to perform the analysis in R. For both models the inverse variance method is .
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META-R (Multi Environment Trail Analysis with R for ~ META-R is a set of R programs that performs statistical analyses to calculate BLUEs, BLUPs, genetic correlations among locations and genetic correlations between variables, broad-sense heritability, and other statistics for breeding trials are given too, in order to make boxplots and histograms. Analyses may be performed by location, across management conditions or across all locations.
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Which meta-analysis software is easy to use ~ Metafor in R is very powerful for conducting meta analysis. It largely depends on the type of analysis and details that you need, but technically it is not that hard to run a meta analysis in .
(PDF) A Practical Tutorial on Conducting Meta-Analysis in R ~ Meta-analysis is a set of statistical procedures used for providing transparent, objective, and replicable summaries of research findings. This tutorial demonstrates the most common procedures on .
Meta-Analysis with R / SpringerLink ~ This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis.
Meta Analysis With R / R (Programming Language) / Command ~ G. Schwarzer et al., Meta-Analysis with R, Use R!, DOI 10.1007/978-3-319-21416-0_2 22 2 Fixed Effect and Random Effects Meta-Analysis difference. In Sect. 2.6, the generic inverse variance method is applied in meta- analyses with survival outcome, cross-over trials and adjusted estimates from regression models.
How to perform a meta-analysis with R: a practical ~ Objective Meta-analysis is of fundamental importance to obtain an unbiased assessment of the available evidence. In general, the use of meta-analysis has been increasing over the last three decades with mental health as a major research topic. It is then essential to well understand its methodology and interpret its results. In this publication, we describe how to perform a meta-analysis with .
Introductionto Meta-Analysis ~ Meta-analysis methods 344 Example of psychometric meta-analysis 346 Comparison of artifact correction with meta-regression 348 Sources of information about artifact values 349 How heterogeneity is assessed 349 Reporting in psychometric meta-analysis 350 Concluding remarks 351 Summary points 351 PART 9: META-ANALYSIS IN CONTEXT 39 OVERVIEW 355
Doing Meta-Analysis in R - Bookdown ~ Get R and RStudio set for your Meta-Analysis. Get your data into R. Prepare your data for the meta-analysis. Install and use the dmetar R package we built specifically for this guide. Perform fixed-effect and random-effects meta-analysis using the meta and metafor packages. Analyse the heterogeneity of your results.
5.2 Layout types / Doing Meta-Analysis in R ~ 5.2 Layout types. The meta::forest function also has two Layouts preinstalled which we can use. Those layouts can be accessed with the layout parameter. “RevMan5”.This layout is used for Cochrane reviews and generated by Review Manager 5. “JAMA”.This layout gives you a forest plot according to the guidelines of the Journal of the American Medical Association as output (see details here).
A Review of Meta-Analysis Packages in R - ERIC ~ Meta-analysis packages built in R and using the R programming language follow this trend. Chen and Peace’s (2013) and Schwarzer, Carpenter, and Ru¨cker’s (2015b) textbooks described many of the basic R meta-analytic packages, and Neupane, Richer,
meta-analysis / Meta Analysis / R (Programming Language ~ meta-analysis - Free download as PDF File (.pdf), Text File (.txt) or read online for free. Software
Doing Meta-Analysis in R / Protect Lab ~ Our guide “Doing Meta-Analysis in R: A Hands-On Guide” shows you how to conduct meta-analyses in R from scratch. It includes a companion R package, dmetar.. Read the Guide ↗ Download dmetar ↗; Citation. Harrer, M., Cuijpers, P., Furukawa, T.A, & Ebert, D. D. (2019).
Meta-Analysis with R (Use R!): 9783319214153: Medicine ~ This item: Meta-Analysis with R (Use R!) by Guido Schwarzer Paperback $49.03. Only 9 left in stock - order soon. Sold by itemspopularsonlineaindemand and ships from Fulfillment. FREE Shipping. Details. Common Mistakes in Meta-Analysis and How to Avoid Them by Michael Borenstein Paperback $68.00.
Books on Meta-Analysis ~ This book provides a very clear overview of meta-analysis – what it is, why we use it, how to perform and interpret a meta-analysis, and how to avoid common mistakes. It starts with basic ideas (how to compute an effect size and perform a simple analysis) but then moves on to more advanced issues (subgroups analysis, meta-regression, multiple outcomes, publication bias).
A Review of Meta-Analysis Packages in R - Joshua R ~ Authors. JOSHUA R. POLANIN, PhD, is a senior research scientist at Development Services Group, Inc. (a social science research firm that specializes in training and technical assistance, impact evaluations, and large-scale systematic reviews); 7315 Wisconsin Ave., Suite 840, Bethesda, MD 20814; email: [email protected] com.His areas of expertise are in adolescent health and well-being, school .
How to perform a meta-analysis with R: a practical tutorial ~ Install R packages for meta-analysis. Conduct a meta-analysis when the outcome of interest is binary. Assess the impact of missing outcome data. Assess and account for small-study effects. MeThOdS Before conducting a meta-analysis, the R packages meta and metasens need to be installed,9 which include all functions to perform the analyses and
Use R! An Introduction to Meta-Analysis with R ~ Objectives: Drawing on our forthcoming book 'Meta-Analysis with R', part of the Use R!-series by Springer, this course will: - provide a brief introduction to R (getting started: R as a calculator; getting help; importing data from RevMan; R packages for meta-analysis).
Analysis Examples [The metafor Package] ~ Meta-Analysis of 2×2 Tables and Person-Time Data using the Mantel-Haenszel Method The use of the Mantel-Haenszel method for meta-analyzing risk differences, risk ratios, and odds ratios (for 2×2 table data) and for meta-analyzing incidence rate differences and incidence rate ratios (for two-group person-time data) is illustrated in the following article.
Free Applied Meta-Analysis with R Download / Books Download ~ Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R.