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Conference Papers Year : 2023

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

Abstract

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
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Dates and versions

hal-04263354 , version 1 (28-10-2023)

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Damien Masson, Sylvain Malacria, Géry Casiez, Daniel Vogel. Statslator: Interactive Translation of NHST and Estimation Statistics Reporting Styles in Scientific Documents. UIST '23: The 36th Annual ACM Symposium on User Interface Software and Technology, ACM, Oct 2023, San Francisco CA, United States. pp.1-14, ⟨10.1145/3586183.3606762⟩. ⟨hal-04263354⟩
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