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Implementing experiments in paper titled "Targeted Machine Learning for Average Causal Effect Estimation Using the Front-Door Functional"

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Implementation of experiments

Simulations

This folder contains code for implementing the simulation studies discussed in the paper. The four folders, namely sim1-consistency, sim2-weak-overlap, sim3-misspecification, and sim4-crossfitting, correspond to the four subsections on simulation in the paper.

FOLDERS

  • binaryM is the univariate binary mediator folder.

  • continuousM is the univariate continuous mediator folder.

  • multiM-d2 is the bivariate mediator folder.

  • multiM-d4 is the four-dimensional mediators folder.

  • DGPs folders contain the data generating code and code for empirically computing the true ACE and its variance. Execute lines in the compute_truth.txt for computing the truth.

  • CF is the Cross Fitting folder.

  • Linear is the estimation with linear regressions folder.

  • SL is the Super Learner folder.

  • RF is the Random Forest folder.

  • Onestep-est1 is the estimation using estimator \psi_1^+ folder.

  • TMLE-est1 is the estimation using estimator \psi_1 folder.

  • Onestep-est2a is the estimation using estimator \psi_{2a}^+ folder.

  • TMLE-est2a is the estimation using estimator \psi_{2a} folder.

  • Onestep-est2b is the estimation using estimator \psi_{2b}^+ folder.

  • TMLE-est2b is the estimation using estimator \psi_{2b} folder.

  • output is the folder that contains estimation results.

FILES

  • joblist*.txt: This is the job file for simulation. Each line corresponding to one simulation. It is recommended to execute the job lists using parallel computing.

  • write_job.R: This is the R script for producing the joblist*.txt files.

  • main.R: Each line in the job list calls this main.R function to perform TMLE and one-step estimation. This file calls the 'fdtmle' package for estimation and save estimation results to the output folders, located under subfolders named after the estimators.

  • organize_onestep.R: This file is used for organizing the output file from one-step estimators. It is called by the organize.txt file within each estimator folder.

  • organize_onestep.R: This file is used for organizing the output file from TMLEs. It is called by the organize.txt file within each estimator folder.

  • organize.txt: This file contains code for summarizing the files in the output folder. Run bash organize.txt in terminal to execute.

  • plot.R: This is used for generating plots for sim1-consistency. This file calls plot-sub.R for generating smaller plots.

  • plot-sub.R: This function is called by the plot.R for generating smaller plots.

  • table.R: This is the R script used for generating tables in the paper.

Real data application

Utilizing our front-door estimation framework, we investigated how early academic achievements influence future annual income. The data for this analysis was sourced from the Life Course Study.

Due to data sharing constraints, we are unable to provide direct access to the raw data used for the real data analysis presented in this study. However, the dataset is available for application through the Finnish Social Science Data Archive

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Implementing experiments in paper titled "Targeted Machine Learning for Average Causal Effect Estimation Using the Front-Door Functional"

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