Yu S C, Wang Q Q, Long X J, Hu Y H, Li J Q, Xiang X L, Shi J X
Office of Epidemiology, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Zhonghua Yu Fang Yi Xue Za Zhi. 2020 Apr 6;54(4):451-456. doi: 10.3760/cma.j.cn112150-20191030-00824.
In general, the application conditions of linear regression models could be met after the natural logarithmic transformation of data. From the practical perspective, this paper introduced the linear regression models with natural logarithmic transformation of independent variable, dependent variable, and both independent and dependent variables in detail. The paper illustrated why the equation and coefficients could not be directly explained after the natural logarithmic transformation of data. The percentage changes of and/or were applied to elaborate the principle and method for the explanation of the equation and coefficients. Three examples were used to fit simple linear models with natural logarithmic transformation of independent, dependent, and both independent and dependent variables and the results of theses models were explained in detail.
一般来说，对数据进行自然对数变换后，线性回归模型的应用条件通常能够得到满足。从实际角度出发，本文详细介绍了自变量、因变量以及自变量和因变量都进行自然对数变换的线性回归模型。本文阐述了数据进行自然对数变换后方程和系数为何不能直接解释。运用自变量和/或因变量的百分比变化来详细说明解释方程和系数的原理及方法。通过三个例子分别拟合自变量、因变量以及自变量和因变量都进行自然对数变换的简单线性模型，并对这些模型的结果进行了详细解释。
