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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Argus: Interactive a priori Power Analysis
Organization Unit
Authors
  • Xiaoyi Wang
  • Alexander Eiselmayer
  • Wendy E Mackay
  • Kasper Hornbæk
  • Chatchavan Wacharamanotham
Item Subtype Original Work
Refereed Yes
Status Published electronically before print/final form (Epub ahead of print)
Language
  • English
Journal Title IEEE Transactions on Visualization and Computer Graphics
Publisher Institute of Electrical and Electronics Engineers
Geographical Reach international
ISSN 1077-2626
Page Range 1 - 111
Date 2021
Abstract Text 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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