Visualizing Uncertainty due to Missing Data

Hanne Ida Oberman
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Hanne Ida Oberman: Utrecht University

No ahtfy, OSF Preprints from Center for Open Science

Abstract: Scientific uncertainty is often omitted from data visualization for communication, while it may enable audiences to assess study results more fairly. One source of uncertainty is of particular interest in this project: missing data. Missingness is ubiquitous, typically ignored, and poses a major threat to the validity of scientific results. We aim to find intuitive ways to express uncertainty due to missing data, and would like your feedback on our online pilot app.

Date: 2021-09-23
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:ahtfy

DOI: 10.31219/osf.io/ahtfy

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