Application of Hierarchical Visualization Techniques in Meta-Analysis Data | IGI Global Scientific Publishing
Application of Hierarchical Visualization Techniques in Meta-Analysis Data

Application of Hierarchical Visualization Techniques in Meta-Analysis Data

Bruna Rossetto Delazeri, Felipe Paes Gusmão, Simone Nasser Matos, Alaine Margarete Guimarães, Marcelo Giovanetti Canteri
Copyright: © 2018 |Volume: 9 |Issue: 1 |Pages: 15
ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781522545200|DOI: 10.4018/IJAEIS.2018010101
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MLA

Delazeri, Bruna Rossetto, et al. "Application of Hierarchical Visualization Techniques in Meta-Analysis Data." IJAEIS vol.9, no.1 2018: pp.1-15. https://doi.org/10.4018/IJAEIS.2018010101

APA

Delazeri, B. R., Gusmão, F. P., Matos, S. N., Guimarães, A. M., & Canteri, M. G. (2018). Application of Hierarchical Visualization Techniques in Meta-Analysis Data. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 9(1), 1-15. https://doi.org/10.4018/IJAEIS.2018010101

Chicago

Delazeri, Bruna Rossetto, et al. "Application of Hierarchical Visualization Techniques in Meta-Analysis Data," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 9, no.1: 1-15. https://doi.org/10.4018/IJAEIS.2018010101

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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.

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