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| Phân tích cỡ mẫu mạnh mẽ× | Phân tích lực (Power Analysis)× | |
|---|---|---|
| Lĩnh vực | Thống kê | Thống kê |
| Họ | Hypothesis test | Hypothesis test |
| Năm ra đời≠ | 2005 (formalized) | 1969 (1st ed.); 1988 (seminal 2nd ed.) |
| Người khởi xướng≠ | Algina, Keselman & Penfield; Wilcox | Jacob Cohen |
| Loại≠ | Robust effect size estimation | Sample size and power planning |
| Công trình gốc≠ | 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 ↗ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 |
| Tên gọi khác | robust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean difference | sample size calculation, power calculation, sensitivity analysis, a priori power analysis |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | 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. | Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study. |
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