ArticlePloS one2026
Visualizing vastness: Graphical methods for multiverse analysis.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.