Materials for replicating the results in "Bayesian Causal Forests for Multivariate Outcomes: Application to Irish Data From an International Large Scale Education Assessment."
The preprint of this article can be found at https://browse.arxiv.org/pdf/2303.04874.pdf
The TIMSS data used in the study is available for download at https://timss2019.org/international-database/
An R package implementing the model from the paper is available at https://nathan-mcjames.github.io/mvbcf/
MVBCF_Code.cpp - RCPP Implementation of Multivariate BCF.
MVBCF_RI_Code.cpp - RCPP Implementation of Multivariate BCF (With Random Intercepts).
GitHub_DGP1.R - Code for evaluating model performance on Data Generating Process 1.
GitHub_DGP2.R - Code for evaluating model performance on Data Generating Process 2.
GitHub_DGP3.R - Code for evaluating model performance on Data Generating Process 3.
GitHub_Desk.R - Code for estimating treatment effects of "Has Study Desk" treatment.
GitHub_Hungry.R - Code for estimating treatment effects of "Often Hungry" treatment.
GitHub_Absent.R - Code for estimating treatment effects of "Often Absent" treatment.
GitHub_Desk_OOS.R - Code for 10-fold cross validation results with "Has Study Desk" treatment.
GitHub_Hungry_OOS.R - Code for 10-fold cross validation results with "Often Hungry" treatment.
GitHub_Absent_OOS.R - Code for 10-fold cross validation results with "Often Absent" treatment.