📦 R/medoutcon: Efficient Causal Mediation Analysis with Natural and Interventional Direct/Indirect Effects
Treatment evaluation in presence of large number of covariates or treatment heterogeneity through Machine Learning methods
Comparing effectiveness of the most common causal machine learning methods across various treatment effect, model complexities, data dimensions and sample sizes.
various causal modeling techniques to determine if living in the U.S. or Europe impacts developers’ overall job satisfaction.
Robust Smooth Heterogeneous Treatment Effect Estimation using Causal Machine Learning
Causal segmentation: estimating conditional average treatment effects for the heterogeneous groups in a sample
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