Statslator: Interactive Translation of NHST and Estimation Statistics Reporting Styles in Scientific Documents

要旨

Inferential statistics are typically reported using p-values (NHST) or confidence intervals on effect sizes (estimation). This is done using a range of styles, but some readers have preferences about how statistics should be presented and others have limited familiarity with alternatives. We propose a system to interactively translate statistical reporting styles in existing documents, allowing readers to switch between interval estimates, p-values, and standardized effect sizes, all using textual and graphical reports that are dynamic and user customizable. Forty years of CHI papers are examined. Using only the information reported in scientific documents, equations are derived and validated on simulated datasets to show that conversions between p-values and confidence intervals are accurate. The system helps readers interpret statistics in a familiar style, compare reports that use different styles, and even validate the correctness of reports. Code and data: https://osf.io/x4ue7

著者
Damien Masson
University of Waterloo, Waterloo, Ontario, Canada
Sylvain Malacria
Univ. Lille, Inria, CNRS, Centrale Lille, UMR 9189 - CRIStAL, Lille, France
Géry Casiez
Univ. Lille, CNRS, Inria, Centrale Lille, UMR 9189 CRIStAL, Lille, France
Daniel Vogel
University of Waterloo, Waterloo, Ontario, Canada
論文URL

https://doi.org/10.1145/3586183.3606762

動画

会議: UIST 2023

ACM Symposium on User Interface Software and Technology

セッション: Data Dreamers: Math, Stats and Visualization

Gold Room
6 件の発表
2023-11-01 18:00:00
2023-11-01 19:20:00