一元线性回归的效应量
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| 两侧同时换到之前的修订记录前一修订版 | |
| 一元线性回归的效应量 [2024/04/19 10:23] – caomingsu | 一元线性回归的效应量 [2024/04/19 10:28] (当前版本) – [The effect size of univariate linear regression] caomingsu |
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| - 一元回归分析常用效应量为**复相关系数R<sup>2</sup>**，它表明了回归方程对因变量的解释能力。\\A commonly used effect size for univariate regression analysis is the compound correlation coefficient R2, which indicates the ability of the regression equation to explain the dependent variable.\\ | - 一元回归分析常用效应量为**复相关系数R<sup>2</sup>**，它表明了回归方程对因变量的解释能力。\\A commonly used effect size for univariate regression analysis is ** the compound correlation coefficient R<sup>2</sup>**, which indicates the ability of the regression equation to explain the dependent variable.\\ |
| - R<sup>2</sup>公式：{{ ::一元线性回归效应量-1.png?200 |}}\\ 或者{{ ::一元线性回归效应量-2.png?150 |}} | - R<sup>2</sup>公式：{{ ::一元线性回归效应量-1.png?200 |}}\\ 或者{{ ::一元线性回归效应量-2.png?150 |}} |
| - 复相关效应量会过高估计自变量对因变量解释能力，现在常用**校正复相关系数R<sup>2</sup><sub>adj</sub>**作为效应量。 | - 复相关效应量会过高估计自变量对因变量解释能力，现在常用**校正复相关系数R<sup>2</sup><sub>adj</sub>**作为效应量。\\Complex correlation effect sizes can overestimate the ability of the independent variable to explain the dependent variable, and it is now common to use **Calibrated Complex Correlation CoefficientR<sup>2</sup><sub>adj</sub>** corrected complex correlation coefficients as effect sizes. |
| - R<sup>2</sup><sub>adj</sub>公式：\\{{ ::校正复相关系数.png?200 |}} | - R<sup>2</sup><sub>adj</sub>公式：{{ ::校正复相关系数.png?200 |}} |
一元线性回归的效应量.1713522238.txt.gz · 最后更改: 2024/04/19 10:23 由 caomingsu
