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| Analisis Ukuran Efek Robust× | ANOVA Satu Arah Robust× | |
|---|---|---|
| Bidang | Statistika | Statistika |
| Keluarga | Hypothesis test | Hypothesis test |
| Tahun asal≠ | 2005 (formalized) | 1951 (Welch); 1990s–2000s (trimmed-mean variants) |
| Pencetus≠ | Algina, Keselman & Penfield; Wilcox | B. L. Welch; R. R. Wilcox (trimmed-mean extension) |
| Tipe≠ | Robust effect size estimation | Robust parametric group comparison |
| Sumber perintis≠ | Algina, J., Keselman, H. J., & Penfield, R. D. (2005). An alternative to Cohen's standardized mean difference effect size: A robust parameter and confidence interval in the two independent groups case. Psychological Methods, 10(3), 317–328. DOI ↗ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 |
| Alias | robust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean difference | trimmed-mean ANOVA, Welch one-way ANOVA, heteroscedastic one-way ANOVA, robust ANOVA |
| Terkait≠ | 5 | 2 |
| Ringkasan≠ | Robust effect size analysis quantifies the magnitude of a difference or association using estimators that are resistant to outliers and violations of normality. Rather than relying on classical statistics such as Cohen's d based on sample means and standard deviations, robust variants use trimmed means and Winsorized standard deviations to produce effect size estimates that accurately reflect the typical effect rather than being inflated by extreme values. | Robust one-way ANOVA compares the central tendency of three or more independent groups while resisting the distorting effects of outliers and heterogeneous variances. By replacing ordinary means with trimmed means and ordinary variances with Winsorized variances, it maintains accurate Type I error control and strong power when classical ANOVA assumptions are violated. |
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