Adapting CCDF Plots for Visualizing Ordinal Regression Results
Authors
Abhraneel Sarma (Graz University of Technology)
Presentation
- Session
- Form Follows Function
- Time
- Tuesday, Nov 10, 11:03 – 11:12 (US/Eastern) · session 10:00 – 11:30
- Location
- Hall Essex north
Links
Sign in to access the preprint PDF.
Sign in- Download Supplemental Material
Keywords
Complementary Cumulative Distribution Functions, Likert scale, Ordinal Regression Model
Abstract
Cumulative-link ordinal regression models are an alternative approach for analysing ordinal data such as Likert items, which are widely used in Visualization (and other related fields like HCI, psychology etc.). There are many researchers who are strong proponents of this approach, as it makes less stringent assumptions about the data, compared to the more commonly used linear model or ANOVA. Yet, ordinal regression models have seen limited adoption. I posit that one possible reason for this might be due to the difficulty in visually representing the results from such models, and in communicating the key takeaways in an intuitive manner. I propose the use of (modified) Complementary Cumulative Distribution Function (mCCDF) plots to visualize the results of ordinal regression models, and demonstrate how the same takeaways that researchers present from analyses which treat ordinal data as metric can be easily communicated using mCCDFs.
For Practitioners
Visualization, HCI and researchers from other fields such as social sciences who conduct collect data using Likert scales