Argus: Interactive a priori Power Analysis
This addresses the problem of experiment design for HCI researchers by providing an interactive tool for power analysis, though it is incremental as it builds on existing statistical methods with a new interface.
The researchers tackled the challenge of determining appropriate sample sizes for controlled experiments in HCI by developing Argus, a tool that enables interactive exploration of statistical power through simulations and visualizations, allowing researchers to make informed decisions based on varying design scenarios.
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.