The inverse hyperbolic sine transformation and retransformed marginal effects
The inverse hyperbolic sine transformation and retransformed marginal effects
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反双曲正弦变换和重新变换的边际效应
DOI：
10.1177/1536867x221124553
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
E. Norton
中科院分区：
文献类型：
--
作者：
E. Norton
在这篇文章中，我将展示如何在估计一个线性回归后，在Stata中计算结果变量的原始尺度上的一致边际效应，该线性回归的因变量已被反双曲正弦函数转换。该方法使用的误差项的非参数再变换和帐户的因变量的任何缩放。反双曲正弦函数对缩放不是不变的，已知当所有观测值为正时，缩放会将未变换因变量的边际效应转换为对数变换因变量的边际效应。
In this article, I show how to calculate consistent marginal effects on the original scale of the outcome variable in Stata after estimating a linear regression with a dependent variable that has been transformed by the inverse hyperbolic sine function. The method uses a nonparametric retransformation of the error term and accounts for any scaling of the dependent variable. The inverse hyperbolic sine function is not invariant to scaling, which is known to shift marginal effects between those from an untransformed dependent variable to those of a logtransformed dependent variable, when all observations are positive.