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Journal Articles IEEE Transactions on Visualization and Computer Graphics Year : 2021

Argus: Interactive A Priori Power Analysis

Abstract

A key challenge HCI researchers face when designing a controlled experiment is choosing the appropriate number of participants, or sample size. A priori power analysis examines the relationships among multiple parameters, including the complexity associated with human participants, e.g., order and fatigue effects, to calculate the statistical power of a given experiment design. We created Argus, a tool that supports interactive exploration of statistical power: Researchers specify experiment design scenarios with varying confounds and effect sizes. Argus then simulates data and visualizes statistical power across these scenarios, which lets researchers interactively weigh various trade-offs and make informed decisions about sample size. We describe the design and implementation of Argus, a usage scenario designing a visualization experiment, and a think-aloud study.
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Dates and versions

hal-03153651 , version 1 (26-02-2021)

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Xiaoyi Wang, Alexander Eiselmayer, Wendy E. Mackay, Kasper Hornbaek, Chat Wacharamanotham. Argus: Interactive A Priori Power Analysis. IEEE Transactions on Visualization and Computer Graphics, 2021, Transactions on Visualization and Computer Graphics, 27 (2), pp.432-442. ⟨10.1109/TVCG.2020.3028894⟩. ⟨hal-03153651⟩
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