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Type | Journal Article |
Scope | Discipline-based scholarship |
Title | Argus: Interactive a priori Power Analysis |
Organization Unit | |
Authors |
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Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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Journal Title | IEEE Transactions on Visualization and Computer Graphics |
Publisher | Institute of Electrical and Electronics Engineers |
Geographical Reach | international |
ISSN | 1077-2626 |
Volume | 27 |
Number | 2 |
Page Range | 432 - 442 |
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. |
Free access at | Related URL |
Related URLs |
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Digital Object Identifier | 10.1109/TVCG.2020.3028894 |
Other Identification Number | merlin-id:19785 |
PDF File | Download from ZORA |
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