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HOIF Estimator Computation Update

Update - 2024-12-19 📢

The higher-order (now up to the sixth order) computation code for the HOIF (sHOIF/eHOIF) estimator has been updated and is now available in the "HOIF_function" folder.

Update - 2024-12-16 📢

The higher-order (now up to the fifth order) computation code for the HOIF (sHOIF/eHOIF) estimator has been updated and is now available in the "HOIF_function" folder.

Falsification using higher order influence functions for double machine learning estimators of causal effects

Introduction

Here we provide the code to reproduce the analysis described in:

Organization

  • create_simulation_parameters_continuous_X.R — simulates training and oracle samples, fits nuisance parameters models in the training sample, and computes inverse Gram matrices for the simulation with continuous X.
  • continuous_X_sim.R — simulates estimation samples, computes estimates of counterfactual means, and computes second order bias estimates for the simulation with continuous X.
  • continuous_X_sim_choose_stopping_k.R — uses the approach described in the supplement to choose k for simulation with continuous X.
  • create_simulation_parameters_binary_X.R — simulates training and oracle samples, fits nuisance parameters models in the training sample, and computes inverse Gram matrices for the simulation with binary X.
  • binary_X_sim.R — simulates estimation samples, computes estimates of counterfactual means, and computes second order bias estimates for the simulation with binary X.
  • compute_bias_all_sims.R — computes the conditional bias, and the Cauchy-Schwarz bias for simulations with binary and continuous X.
  • create_simulation_parameters_CRC_GAN_data.R — simulates training and oracle samples, fits nuisance parameters models in the training sample, and computes inverse Gram matrices for the simulation with artificial data based on the National Cancer Database.
  • CRC_GAN_sim.R — simulates estimation samples, computes estimates of counterfactual means, and computes second order bias estimates for the simulation with artificial data based on the National Cancer Database.
  • create_parameters_CRC_real_data.R — sample splits, fits nuisance parameters models, and computes inverse Gram matrices for analysis of the National Cancer Database.
  • CRC_real_data_analysis.R — computes cross-fit estimates of counterfactual means (and the risk difference), and estimates of the second order bias.
  • CRC_real_data_analysis_choose_stopping_k.R — uses the approach described in the supplement to choose k for analysis of the National Cancer Database.
  • process_outputs.R — R file which reproduces the tables and figures displayed in the main text, summarizing simulation results.
  • process_outputs_supplement.R — R file which reproduces the tables and figures displayed in the supplement, summarizing simulation results.
  • src — Folder containing scripts with functions and dependencies to be called by the above files.
  • params — Folder should be created to which simulation parameters, which are outputs of create_simulation_parameters..., are saved.
  • output — Folder to which simulation outputs are saved.
  • figures — Folder containing figures, which are outputs of process_outputs.R and process_outputs_supplement.R.

Correspondence

If you have any questions, comments, or discover an error, please contact Kerollos Wanis at [email protected].