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
LEADER 04444nam a2200541 4500
001 978-94-024-1696-1
003 DE-He213
005 20191027033033.0
007 cr nn 008mamaa
008 190507s2019 ne | s |||| 0|eng d
020 |a 9789402416961  |9 978-94-024-1696-1 
024 7 |a 10.1007/978-94-024-1696-1  |2 doi 
040 |d GrThAP 
050 4 |a S1-S972 
072 7 |a TVB  |2 bicssc 
072 7 |a TEC003000  |2 bisacsh 
072 7 |a TVB  |2 thema 
082 0 4 |a 630  |2 23 
100 1 |a Makowski, David.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a From Experimental Network to Meta-analysis  |h [electronic resource] :  |b Methods and Applications with R for Agronomic and Environmental Sciences /  |c by David Makowski, François Piraux, François Brun. 
250 |a 1st ed. 2019. 
264 1 |a Dordrecht :  |b Springer Netherlands :  |b Imprint: Springer,  |c 2019. 
300 |a X, 155 p. 69 illus., 43 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
505 0 |a 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. 
520 |a 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 on different experimental protocols, are generally heterogeneous. Sometimes they are not even directly accessible and should be extracted from scientific articles or reports. However, a comprehensive analysis of the available data is essential to increase the accuracy of estimates, assess the validity of research conclusions and understand the origin of the variability of the experimental results. A quantitative synthesis of the data set available allows for a better understanding of the effects of explanatory factors and for evidence-based recommendations. Designed as a methodological guide, this book 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. Our objective is to present the main statistical methods to analyze data from experimental networks and scientific publications. Each chapter exposes one or more methods and illustrates them with examples processed with the R software. Data and R codes are provided and commented in order to facilitate their adaptation to other situations. The codes can be reused from the KenSyn R package associated with this book. 
650 0 |a Agriculture. 
650 0 |a Plant science. 
650 0 |a Botany. 
650 0 |a Statistics . 
650 0 |a Environmental sciences. 
650 1 4 |a Agriculture.  |0 http://scigraph.springernature.com/things/product-market-codes/L11006 
650 2 4 |a Plant Sciences.  |0 http://scigraph.springernature.com/things/product-market-codes/L24000 
650 2 4 |a Statistical Theory and Methods.  |0 http://scigraph.springernature.com/things/product-market-codes/S11001 
650 2 4 |a Environmental Science and Engineering.  |0 http://scigraph.springernature.com/things/product-market-codes/G37000 
700 1 |a Piraux, François.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Brun, François.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9789402416954 
776 0 8 |i Printed edition:  |z 9789402416978 
776 0 8 |i Printed edition:  |z 9789402416985 
856 4 0 |u https://doi.org/10.1007/978-94-024-1696-1  |z Full Text via HEAL-Link 
912 |a ZDB-2-SBL 
950 |a Biomedical and Life Sciences (Springer-11642)