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Estimation of marginal effects for models with alternative variable transformations
The Stata Journal: Promoting communications on statistics and Stata ( IF 4.8 ) Pub Date : 2021-03-30 , DOI: 10.1177/1536867x211000005
Fernando Rios-Avila 1
Affiliation  

margins is a powerful postestimation command that allows the estimation of marginal effects for official and community-contributed commands, with well-defined predicted outcomes (see predict). While the use of factor-variable notation allows one to easily estimate marginal effects when interactions and polynomials are used, estimation of marginal effects when other types of transformations such as splines, logs, or fractional polynomials are used remains a challenge. In this article, I describe how margins‘s capabilities can be extended to analyze other variable transformations using the command f_able.



中文翻译:

具有替代变量变换的模型的边际效应估计

margins是一个功能强大的后估计命令,可用于估计官方和社区贡献的命令的边际效果,并具有明确定义的预测结果(请参见predict)。尽管使用因子变量表示法可以轻松地估计使用交互作用和多项式时的边际效应,但是使用其他类型的转换(例如样条,对数或分数多项式)时边际效应的估计仍然是一个挑战。在本文中,我描述了如何使用命令f_able扩展margins的功能以分析其他变量转换。

更新日期:2021-03-30
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