So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Phân tích phương sai Biến đổi Hạng Liên kết (ART-ANOVA)× | ANOVA mạnh mẽ (Trung bình cắt tỉa & Welch)× | |
|---|---|---|
| Lĩnh vực | Thống kê | Thống kê |
| Họ≠ | Hypothesis test | Regression model |
| Năm ra đời≠ | 2011 | 1951 |
| Người khởi xướng≠ | Wobbrock, Findlater, Gergle & Higgins | Welch (1951); robust trimmed-mean approach popularised by Wilcox |
| Loại≠ | Nonparametric factorial hypothesis test | Robust one-way analysis of variance |
| Công trình gốc≠ | 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 ↗ |
| Tên gọi khác≠ | 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) |
| Liên quan≠ | 7 | 5 |
| Tóm tắt≠ | 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. |
| ScholarGateBộ dữ liệu ↗ |
|
|