Meta-Analysis with R (eBook, PDF) - Schwarzer, Guido; Carpenter, James R.; Rücker, Gerta
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Produktbeschreibung
Autorenporträt
Inhaltsangabe

Part I Getting Started: An Introduction to Meta-Analysis in R.- Part II Standard Methods: Fixed Effect and Random Effects Meta-Analysis.- Meta-Analysis with Binary Outcomes.- Heterogeneity and Meta-Regression.- Part III Advanced Topics: Small-Study Effects in Meta-Analysis.- Missing Data in Meta-Analysis.- Multivariate Meta-Analysis.- Network Meta-Analysis.- Meta-Analysis of Diagnostic Test Accuracy Studies.- Further Information on R.- Index.
Rezensionen
"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)