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Cited by 2,854

The DOI matches its Crossref record.

The aligned rank transform for nonparametric factorial analyses using only anova procedures

Wobbrock, Jacob O., Findlater, Leah, Gergle, Darren, Higgins, James J.·2011·Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
DOI 10.1145/1978942.1978963
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Abstract

Nonparametric data from multi-factor experiments arise often in human-computer interaction (HCI). Examples may include error counts, Likert responses, and preference tallies. But because multiple factors are involved, common nonparametric tests (e.g., Friedman) are inadequate, as they are unable to examine interaction effects. While some statistical techniques exist to handle such data, these techniques are not widely available and are complex. To address these concerns, we present the Aligned Rank Transform (ART) for nonparametric factorial data analysis in HCI. The ART relies on a preprocessing step that "aligns" data before applying averaged ranks, after which point common ANOVA procedures can be used, making the ART accessible to anyone familiar with the F-test. Unlike most articles on the ART, which only address two factors, we generalize the ART to N factors. We also provide ARTool and ARTweb, desktop and Web-based programs for aligning and ranking data. Our re-examination of some published HCI results exhibits advantages of the ART.

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Research works printed but not linked: 14

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Metadata

Authors
Wobbrock, J. O., Findlater, L., Gergle, D., & Higgins, J. J.
Venue
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2011-05-07
Pages
143-146
DOI
10.1145/1978942.1978963
OpenAlex
W2128213565
Cited by
2,854
References
0
FWCI
89.08
Type
conference paper
Language
en
Open access
closed
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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