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Treffer: Visualizing vastness: Graphical methods for multiverse analysis.

Title:
Visualizing vastness: Graphical methods for multiverse analysis.
Authors:
Krähmer D; Department of Sociology, University of Munich, Munich, Germany., Young C; Department of Sociology, Cornell University, Ithaca, New York, United States of America.
Source:
PloS one [PLoS One] 2026 Feb 05; Vol. 21 (2), pp. e0339452. Date of Electronic Publication: 2026 Feb 05 (Print Publication: 2026).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Imprint Name(s):
Original Publication: San Francisco, CA : Public Library of Science
MeSH Terms:
Computer Graphics*, Software ; Humans ; Computer Simulation
References:
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Entry Date(s):
Date Created: 20260205 Date Completed: 20260205 Latest Revision: 20260209
Update Code:
20260209
PubMed Central ID:
PMC12875576
DOI:
10.1371/journal.pone.0339452
PMID:
41642923
Database:
MEDLINE

Weitere Informationen

Multiverse analysis is an increasingly popular tool for improving the robustness and transparency of empirical research. Yet, visualization techniques for multiverse analysis are underdeveloped. We identify critical weaknesses in existing multiverse visualizations-specification curves and density plots-and introduce a novel alternative: multiverse plots. Using both simulated and real-world data, we illustrate how multiverse plots can retain detailed information even in the face of thousands of model specifications. Multiverse plots overcome key limitations of existing methods by eliminating arbitrary sampling (a common issue with specification curves) and information loss on analytical decisions (an issue with density plots). Furthermore, they effectively show what conclusions a dataset can reasonably support and which researcher decisions drive variation in results. By providing software code to generate multiverse plots in Stata and R, we enable analysts to visualize multiverse results transparently and comprehensively.
(Copyright: © 2026 Krähmer, Young. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The authors have declared that no competing interests exist.