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Meta-analysis with R

Carpenter, James R.

Meta-analysis with R

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Meta-analysis with Rby Guido Schwarzer, James R. Carpenter, Gerta Rucker.
作者:	Schwarzer, Guido.
其他作者:	Carpenter, James R.
出版者:	Cham :Springer International Publishing :2015.
面頁冊數:	xii, 252 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Meta-analysis.
電子資源:	http://dx.doi.org/10.1007/978-3-319-21416-0
ISBN:	9783319214160$q(electronic bk.)

Meta-analysis with R
Schwarzer, Guido.

Meta-analysis with R[electronic resource] /by Guido Schwarzer, James R. Carpenter, Gerta Rucker. - Cham :Springer International Publishing :2015. - xii, 252 p. :ill., digital ;24 cm. - Use R!,2197-5736. - Use R!.

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.

ISBN: 9783319214160$q(electronic bk.)

Standard No.: 10.1007/978-3-319-21416-0doiSubjects--Topical Terms:

224398
Meta-analysis.

LC Class. No.: R853.M48

Dewey Class. No.: 610.727

Meta-analysis with R
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520 $a 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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