From Experimental Network to Meta-analysis
Methods and Applications with R for Agronomic and Environmental Sciences
Published on 17. May 2019
Book
Hardback
X, 155 pages
978-94-024-1695-4 (ISBN)
Description
This book has been designed as a methodological guide and shows the interests and limitations of different statistical methods to analyze data from experimental networks and to perform meta-analyses. It is intended for engineers, students and researchers involved in data analysis in agronomy and environmental science.
Reviews / Votes
"I would recommend the Meta-analysis in medical research book, or the R meta-analysis tutorials that compare different R packages." (Ramzi El Feghali, ISCB News, iscb.info, Issue 69, July, 2020)
More details
Edition
2019 ed.
Language
English
Place of publication
Dordrecht
Netherlands
Target group
Professional and scholarly
Illustrations
26 s/w Abbildungen, 43 farbige Abbildungen
X, 155 p. 69 illus., 43 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 15 mm
Weight
455 gr
ISBN-13
978-94-024-1695-4 (9789402416954)
DOI
10.1007/978-94-024-1696-1
Schweitzer Classification
Other editions
Additional editions
David Makowski
From Experimental Network to Meta-Analysis
Methodas & Applications with R for Agronomic & Environmental Sciences
Book
05/2019
Springer
€115.50
Shipment within 15-20 days
David Makowski | François Piraux | François Brun
From Experimental Network to Meta-analysis
Methods and Applications with R for Agronomic and Environmental Sciences
E-Book
05/2019
1st Edition
Springer
€149.79
Available for download
Content
Chapter 1. Introduction and examples.- Part I. Analysis of experimental networks.- Chapter 2. Basic Concepts.- Chapter 3. Analysis of network of experiments in blocks of complete randomness as a studied factor.- Chapter 4. Advanced Methods for Network Analysis.- Chapter 5. Planning an Experimental Network.- Part II. The meta-analysis.- Chapter 6. Basics for meta-analysis.- Chapter 7. Specific statistical problems for the meta-analysis.- Annex. R resources to implement the methods of analysis networks and meta-analysis.- Package Codes.