Argus: Interactive a priori Power Analysis
September 16, 2020 Β· Declared Dead Β· π IEEE Transactions on Visualization and Computer Graphics
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Authors
Xiaoyi Wang, Alexander Eiselmayer, Wendy E. Mackay, Kasper Hornbæk, Chat Wacharamanotham
arXiv ID
2009.07564
Category
cs.HC: Human-Computer Interaction
Citations
8
Venue
IEEE Transactions on Visualization and Computer Graphics
Last Checked
4 months ago
Abstract
A key challenge HCI researchers face when designing a controlled experiment is choosing the appropriate number of participants, or sample size. A prior 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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