This repository includes three sets of code related to g-computation:
1: Chapter 13 from the What If Causal Inference Textbook (https://miguelhernan.org/whatifbook): File: chapter13.R Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC
2: Code from the "Simulating the impact of greenspace exposure on metabolic biomarkers in a diverse population living in San Diego, California: A g-computation application" paper File: GSpace_MetS_Gcomp.zip Teyton, A., Nukavarapu, N., Letellier, N., Sears, D. D., Yang, J. A., Jankowska, M. M., & Benmarhnia, T. (2024). Simulating the impact of greenspace exposure on metabolic biomarkers in a diverse population living in San Diego, California: A g-computation application. Environmental Epidemiology, 8(4), e326.
3: Code from the "Using Parametric g-Computation to Estimate the Effect of Long-Term Exposure to Air Pollution on Mortality Risk and Simulate the Benefits of Hypothetical Policies: The Canadian Community Health Survey Cohort (2005 to 2015)" paper File: AP_Mortality_Gcomp.zip Chen, C., Chen, H., van Donkelaar, A., Burnett, R. T., Martin, R. V., Chen, L., ... & Benmarhnia, T. (2023). Using parametric g-computation to estimate the effect of long-term exposure to air pollution on mortality risk and simulate the benefits of hypothetical policies: the Canadian Community Health Survey cohort (2005 to 2015). Environmental Health Perspectives, 131(3), 037010.
If you have any questions or need help accessing the papers/ textbook, please feel free to contact me at ateyton@ucsd.edu. Thanks!