Berry D A
Biometrics. 1987 Jun;43(2):439-56.
A method is presented for choosing an additive constant c when transforming data x to y = log(x + c). The method preserves Type I error probability and power in ANOVA under the assumption that the x + c for some c are log-normally distributed. The method has advantages similar to those of rank transformations--namely, it is easy to use and is resistant to extreme observations. Since the special case c----infinity corresponds in ANOVA to y = x, the method is a useful generalization of least squares.
提出了一种在将数据x转换为y = log(x + c)时选择加性常数c的方法。在某些c对应的x + c呈对数正态分布的假设下,该方法在方差分析中保持了I型错误概率和检验功效。该方法具有与秩变换类似的优点——即易于使用且对极端观测值具有抗性。由于在方差分析中c趋于无穷大的特殊情况对应于y = x,因此该方法是最小二乘法的一种有用推广。