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Phân tích cỡ mẫu mạnh mẽ×Phân tích cỡ hiệu ứng×
Lĩnh vựcThống kêThống kê
HọHypothesis testHypothesis test
Năm ra đời2005 (formalized)1969 (first edition); 1988 (definitive second edition)
Người khởi xướngAlgina, Keselman & Penfield; WilcoxJacob Cohen
LoạiRobust effect size estimationStandardized magnitude estimation
Công trình gốcAlgina, 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 ↗Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
Tên gọi khácrobust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean differenceeffect magnitude estimation, standardized effect measure, practical significance analysis, ES analysis
Liên quan54
Tóm tắtRobust 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.Effect size analysis quantifies the practical magnitude of a statistical result independently of sample size. Rather than asking only whether a difference or relationship is statistically significant, it asks how large it is, using standardized indices such as Cohen's d, eta-squared, omega-squared, or Pearson's r that allow direct comparison across studies and populations.
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ScholarGateSo sánh phương pháp: Robust Effect Size Analysis · Effect size analysis. Truy cập ngày 2026-06-15 từ https://scholargate.app/vi/compare