From Experimental Network to Meta-analysis Methods and Applications with R for Agronomic and Environmental Sciences /

Data analysis plays an increasing role in research, scientific expertise and prospective studies. Multiple data sources are often available to estimate a key parameter or to test a hypothesis of scientific or societal interest. These data, obtained under different environmental conditions or based o...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Makowski, David (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Piraux, François (http://id.loc.gov/vocabulary/relators/aut), Brun, François (http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Dordrecht : Springer Netherlands : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.