Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Ανάλυση Εύρους Επίδρασης (Robust Effect Size Analysis)× | Ανθεκτική ανεξάρτητη δειγμάτων t-δοκιμή× | |
|---|---|---|
| Πεδίο | Στατιστική | Στατιστική |
| Οικογένεια | Hypothesis test | Hypothesis test |
| Έτος προέλευσης≠ | 2005 (formalized) | 1974–1990s |
| Δημιουργός≠ | Algina, Keselman & Penfield; Wilcox | Rand R. Wilcox; Karen K. Yuen (trimmed-mean form) |
| Τύπος≠ | Robust effect size estimation | Robust parametric mean comparison |
| Θεμελιώδης πηγή≠ | 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 |
| Εναλλακτικές ονομασίες | robust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean difference | Yuen's t-test, trimmed-mean t-test, Winsorized t-test, robust two-sample test |
| Συναφείς≠ | 5 | 2 |
| Σύνοψη≠ | 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. | The robust independent samples t-test compares the central tendency of two independent groups using trimmed means and Winsorized variances, making it substantially less sensitive to outliers and non-normality than the classical Student or Welch t-test. The most widely used form is Yuen's test, which also accommodates unequal variances across groups. |
| ScholarGateΣύνολο δεδομένων ↗ |
|
|