Not logged in.
Quick Search - Contribution
Contribution Details
Type | Conference or Workshop Paper |
Scope | Discipline-based scholarship |
Published in Proceedings | Yes |
Title | A Meta-Analysis of Effect Sizes of CHI Typing Experiments |
Organization Unit | |
Authors |
|
Presentation Type | paper |
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
|
Event Title | Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems |
Event Type | conference |
Event Location | Yokohama, Japan |
Event Start Date | May 8 - 2021 |
Event End Date | May 13 - 2021 |
Place of Publication | New York, NY, USA |
Publisher | ACM Digital Library |
Abstract Text | While designing an HCI experiment, planning the sample size with a priori power analysis is often skipped due to the lack of reference effect sizes. On the one hand, it can lead to a false-negative result, missing the effect that is present in the population. On the other hand, it poses a risk of spending more resources if the number of participants is too high. In this work, I present the reference for small, medium, and large effect sizes for typing experiments based on a meta-analysis of well-cited papers from CHI conference. This effect size ruler can be used to conduct a priori power analysis or assess the magnitude of the found effect. This work also includes comparisons to other fields and conclude with a discussion of the existing issues with reporting practices and data availability. This paper and all data and materials are freely available at https://osf.io/nqzpr. |
Free access at | Related URL |
Related URLs |
|
Digital Object Identifier | 10.1145/3411763.3451520 |
Other Identification Number | merlin-id:21051 |
PDF File | Download from ZORA |
Export |
BibTeX
EP3 XML (ZORA) |