手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| クラスター頑健標準誤差× | 順列検定(ランダム化検定)× | |
|---|---|---|
| 分野 | 統計学 | 統計学 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1986 | 2005 |
| 提唱者≠ | Liang & Zeger (GEE sandwich); Cameron & Miller (practitioner synthesis) | Good (2005); Edgington & Onghena (2007); resampling tradition |
| 種類≠ | Robust variance estimation for regression | Nonparametric resampling test |
| 原典≠ | 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 |
| 別名 | clustered standard errors, cluster-robust inference, clustered variance estimator, Küme Robust Standart Hatalar | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| 関連≠ | 4 | 5 |
| 概要≠ | 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. |
| ScholarGateデータセット ↗ |
|
|