TY - GEN
T1 - The Aligned Rank Transform for nonparametric factorial analyses using only ANOVA procedures
AU - Wobbrock, Jacob O.
AU - Findlater, Leah
AU - Gergle, Darren
AU - Higgins, James J.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - ANOVA
KW - Analysis of variance
KW - F-test
KW - Factorial analysis
KW - Nonparametric data
KW - Statistics
UR - http://www.scopus.com/inward/record.url?scp=79958126664&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79958126664&partnerID=8YFLogxK
U2 - 10.1145/1978942.1978963
DO - 10.1145/1978942.1978963
M3 - Conference contribution
AN - SCOPUS:79958126664
SN - 9781450302289
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 143
EP - 146
BT - CHI 2011 - 29th Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings and Extended Abstracts
PB - Association for Computing Machinery
ER -