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| 정렬 순위 변환 분산 분석 (ART-ANOVA)× | 강건 ANOVA (Welch 및 절사 평균)× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열≠ | Hypothesis test | Regression model |
| 기원 연도≠ | 2011 | 1951 |
| 창시자≠ | Wobbrock, Findlater, Gergle & Higgins | Welch (1951); robust trimmed-mean approach popularised by Wilcox |
| 유형≠ | Nonparametric factorial hypothesis test | Robust one-way analysis of variance |
| 원전≠ | Wobbrock, J. O., Findlater, L., Gergle, D., & Higgins, J. J. (2011). The aligned rank transform for nonparametric factorial analyses using only ANOVA procedures. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI 2011), 143–146. DOI ↗ | Welch, B. L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336. DOI ↗ |
| 별칭≠ | ART-ANOVA, aligned ranks ANOVA, nonparametric factorial ANOVA, Hizalanmış Sıra Dönüşümü ANOVA (ART-ANOVA) | Welch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean) |
| 관련≠ | 7 | 5 |
| 요약≠ | The Aligned Rank Transform ANOVA (ART-ANOVA) is a nonparametric factorial hypothesis test that detects main effects and interactions in designs with two or more independent variables, without requiring normality. The procedure was formalized by Wobbrock, Findlater, Gergle, and Higgins in their 2011 CHI paper and operates by separately aligning each effect before ranking, so that standard ANOVA machinery can be applied to nonparametric data. | Robust ANOVA compares the central tendency of three or more groups when the classical assumptions of normality and equal variances fail. It combines Welch's heteroscedasticity-adjusted statistic, introduced by Welch in 1951, with trimmed-mean tests advanced by Wilcox, giving reliable comparisons in the presence of outliers and unequal group spreads. |
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