Dataset and codes for learning regression analysis in management studies

These datasets and codes present regression analyses used in management studies to introduce management scholars to data science. First, I describe the backdoor criterion, which is helpful for variable selection to identify causal effects. Next, I describe interaction models and hierarchical Bayesian models as the regression models in which effects vary across individuals. Finally, I introduce causal effect estimation using machine learning to use regression models for prediction.

本数据集及代码展示了在管理学研究中被广泛应用的回归分析方法，旨在引导管理学者步入数据科学领域。首先，我将对后门准则进行阐述，该准则有助于变量选择以识别因果关系。随后，我将介绍交互模型和分层贝叶斯模型作为回归模型，其中效应随个体而异。最后，我将引入利用机器学习进行因果效应估计的方法，以预测回归模型。