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March 25, 2026Quantitative Science StudiesOpen Access

Introducing multiverse analysis to bibliometrics: The case of team size effects on disruptive research

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Authors

CLChristian LeibelLBLutz Bornmann

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Overview

Multiverse analysis demonstrates team size impacts disruptive research outcomes, indicating importance for bibliometric evaluation.

Key Points

  • The study aims to evaluate the robustness of bibliometric findings regarding team size's effect on disruptive research.
  • Introduced multiverse analysis as a statistical tool for bibliometrics.
  • Conducted robustness checks across multiple plausible models.
  • Assessed the findings of Wu et al. (2019) regarding team size and disruption scores.
  • Found consistent evidence of a negative effect of team size on disruption scores.
  • Effect size varied significantly with different model specifications.
  • Highlight the necessity of examining multiverse robustness for bibliometric findings.

Cite This Study

Leibel et al. (2026) studied this question.

synapsesocial.com/papers/69c37bd4b34aaaeb1a67e985https://doi.org/10.1162/qss.a.475
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Also Consider

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  1. 1Specification uncertainty: What the disruption index tells us about the (hidden) multiverse of bibliometric indicators2024 · 9 citations
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  5. 5Beyond beyond standardization: studying robustness of empirical claims based on topic modeling through multiverse analysis2026