方法对比
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| 聚类稳健标准误× | 置换 (随机化) 检验× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1986 | 2005 |
| 提出者≠ | Liang & Zeger (GEE sandwich); Cameron & Miller (practitioner synthesis) | Good (2005); Edgington & Onghena (2007); resampling tradition |
| 类型≠ | Robust variance estimation for regression | Nonparametric resampling test |
| 开创性文献≠ | Liang, K. Y. & Zeger, S. L. (1986). Longitudinal Data Analysis Using Generalized Linear Models. Biometrika, 73(1), 13-22. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| 别名 | clustered standard errors, cluster-robust inference, clustered variance estimator, Küme Robust Standart Hatalar | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| 相关≠ | 4 | 5 |
| 摘要≠ | Cluster-robust standard errors correct the variance of regression coefficients when observations are correlated within clusters such as schools, hospitals, or regions. The clustered sandwich estimator grew out of Liang & Zeger's (1986) generalized estimating equations and was synthesized for applied work by Cameron & Miller (2015), delivering valid inference when ordinary standard errors would be too small. | The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value. |
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