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 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.
Keywords
Cite
@article{arxiv.2009.07564,
title = {Argus: Interactive a priori Power Analysis},
author = {Xiaoyi Wang and Alexander Eiselmayer and Wendy E. Mackay and Kasper Hornbæk and Chat Wacharamanotham},
journal= {arXiv preprint arXiv:2009.07564},
year = {2020}
}