Doing meta-analysis with R : a hands-on guide / Mathias Harrer, [and 3 others].

By:

Harrer, Mathias [author.]

Contributor(s):

Material type: Text

TextPublisher: Boca Raton, Florida : CRC Press, 2022Edition: First editionDescription: xxvi, 474 pages illustrations ; 24 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780367610074

Subject(s):

Additional physical formats: Online version :: Doing meta-analysis with RDDC classification:

610.727 H235d 23

LOC classification:

R853.M48 H37 2022

Contents:

I. Getting started -- Introduction -- Discovering R -- II. Meta-analysis in R -- Effect sizes -- Pooling effect sizes -- Between-study heterogeneity -- Forest plots -- Subgroup analyses -- Meta-regression -- Publication bias -- III. Advanced methods -- "Multilevel" meta-analysis -- Structural equation modeling meta-analysis -- Network meta-analysis -- Bayesian meta-analysis -- IV. Helpful tools -- Power analysis -- Risk of bias plots -- Reporting and reproducibility -- Effect size calculation and conversion.

Summary: "This book serves as an accessible introduction into how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including 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, SEM meta-analysis are also covered. A companion R package, dmetar, is introduced in the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide"-- Provided by publisher.

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Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	Main Library	Circulation Section	CIR 610.727 H235d 2022 (Browse shelf(Opens below))	1-1	Available		029689

Includes bibliographical references and index.

"This book serves as an accessible introduction into how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including 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, SEM meta-analysis are also covered. A companion R package, dmetar, is introduced in the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide"-- Provided by publisher.

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