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

By:

Schwarzer, Guido [author.]

Contributor(s):

Material type: Text

TextSeries: Use R!Publisher: 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 resource

ISBN:

9783319214160

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

519.5 23

LOC classification:

QA276-280

Online 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. .

Holdings ( 1 )
Title notes ( 2 )

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
eBook	e-Library	EBook		Available

Total holds: 0

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. .