Multivariate visualization in observation-based testing

2002 ◽  
Author(s):  
D. Leon ◽  
A. Podgurski ◽  
L.J. White
Keyword(s):  
Multivariate Visualization

Evaluation of Multivariate Visualization on a Multivariate Task

2012 ◽  
Vol 18 (12) ◽  
pp. 2114-2121 ◽  
Author(s):  
M. A. Livingston ◽  
J. W. Decker ◽  
Zhuming Ai
Keyword(s):  
Multivariate Visualization

Multivariate visualization of 3D turbulent flow data

2010 ◽  
Author(s):  
Sheng-Wen Wang ◽  
Victoria Interrante ◽  
Ellen Longmire
Keyword(s):  
Turbulent Flow ◽  
Flow Data ◽  
Multivariate Visualization

scholarly journals Illustrative Multivariate Visualization for Geological Modelling

2018 ◽  
Vol 37 (3) ◽  
pp. 465-477 ◽  
Author(s):  
A. Rocha ◽  
R. C. R. Mota ◽  
H. Hamdi ◽  
U. R. Alim ◽  
M. Costa Sousa
Keyword(s):  
Geological Modelling ◽  
Multivariate Visualization

Multivariate visualization: A Taxonomy and novel visualization methods

2021 ◽  
Author(s):  
Tom O'Kane ◽  
Dustin Fife
Keyword(s):  
Multivariate Analyses ◽  
Research Question ◽  
Zero Order ◽  
Order Effects ◽  
Relative Ease ◽  
Visual Modeling ◽  
Multivariate Visualization ◽  
Research Questions ◽  
Visualization Strategy ◽  
Added Variable Plots

While intuitive visualizations for bivariate analyses are numerous and able to be constructed with relative ease, the same is not true for multivariate analyses. Commonly utilized multivariate visualization strategies are often cognitively taxing for readers and there is little guidance for researchers seeking to decide upon the proper visualization for their analysis. In this paper we seek to rectify these limitations by developing a data analysis taxonomy that allows one to easily identify appropriate visualizations. This taxonomy aims to provide guidance to researchers in their decision-making regarding which multivariate visualization strategy best fits their research question. Our taxonomy classifies research questions into five different categories (zero-order effects, conditioning, moderation, mediation, and clustering), providing example research questions and analyses for each. Throughout, we identify tools appropriate for multivariate visualizations, including ghost lines, added variable plots, and paneling. All these tools are freely available in R through the Flexplot package, as well as in the Visual Modeling module in JASP.

Multivariate visualization of particle data

2019 ◽  
Vol 227 (14) ◽  
pp. 1741-1755 ◽  
Author(s):  
Liang Zhou ◽  
Daniel Weiskopf
Keyword(s):  
Multivariate Visualization
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