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Meta-Analysis with R electronic resource by Guido Schwarzer, James R. Carpenter, Gerta Rücker.

By: Schwarzer, Guido [author.]Contributor(s): Carpenter, James R [author.] | Rücker, Gerta [author.] | SpringerLink (Online service)Material type: TextTextSeries: Use R!Publication details: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XII, 252 p. 58 illus., 4 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319214160Subject(s): Statistics | Biostatistics | Statistics | Statistics for Life Sciences, Medicine, Health Sciences | Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law | BiostatisticsDDC classification: 519.5 LOC classification: QA276-280Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.  .
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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.

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.  .

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