Application of Hierarchical Visualization Techniques in Meta-Analysis Data

Bruna Rossetto Delazeri, Felipe Paes Gusmão, Simone Nasser Matos, Alaine Margarete Guimarães and Marcelo Giovanetti Canteri
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Bruna Rossetto Delazeri: Department of Informatics, State University of Ponta Grossa, Ponta Grossa, Brazil
Felipe Paes Gusmão: Federal Technological University of Parana, Ponta Grossa, Brazil
Simone Nasser Matos: Department of Computer Science, Federal Technological University of Parana, Ponta Grossa, Brazil
Alaine Margarete Guimarães: Department of Computer Science, State University of Ponta Grossa, Ponta Grossa, Brazil
Marcelo Giovanetti Canteri: Department of Agronomy, Londrina State University, Londrina, Brazil

International Journal of Agricultural and Environmental Information Systems (IJAEIS), 2018, vol. 9, issue 1, 1-15

Abstract: The meta-analysis is a probabilistic technique that groups the results of several studies, approaches the same subject and produces a result that summarizes the whole. The results that are displayed in graphical form neither offer interactivity with the user, nor a user-friendly interface and easy comprehension. In order to obtain a visual exploratory analysis with more satisfactory results, there are information visualization techniques applied to map the data in graphical form to broaden the user cognition. This article performs the execution of the meta-analysis, through R software, in order to determine the efficiency of fungicide fluquinconazole when combating Asian soy rust and applies the Technique for the Visualization of Hierarchical Information Structure; the Bifocal Tree, to improve the results displayed by the R through the forest plot graphic.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jaeis0:v:9:y:2018:i:1:p:1-15

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