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Say farewell to bland regression reporting: Three forest plot variations for visualizing linear models

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  • Jonathan Fries
  • Sandra Oberleiter
  • Jakob Pietschnig

Abstract

Regression ranks among the most popular statistical analysis methods across many research areas, including psychology. Typically, regression coefficients are displayed in tables. While this mode of presentation is information-dense, extensive tables can be cumbersome to read and difficult to interpret. Here, we introduce three novel visualizations for reporting regression results. Our methods allow researchers to arrange large numbers of regression models in a single plot. Using regression results from real-world as well as simulated data, we demonstrate the transformations which are necessary to produce the required data structure and how to subsequently plot the results. The proposed methods provide visually appealing ways to report regression results efficiently and intuitively. Potential applications range from visual screening in the model selection stage to formal reporting in research papers. The procedure is fully reproducible using the provided code and can be executed via free-of-charge, open-source software routines in R.

Suggested Citation

  • Jonathan Fries & Sandra Oberleiter & Jakob Pietschnig, 2024. "Say farewell to bland regression reporting: Three forest plot variations for visualizing linear models," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-16, February.
    • Handle: RePEc:plo:pone00:0297033
    DOI: 10.1371/journal.pone.0297033
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    References listed on IDEAS

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    1. Jackson, Christopher H, 2008. "Displaying Uncertainty With Shading," The American Statistician, American Statistical Association, vol. 62(4), pages 340-347.
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