migariane/TutorialCausalInferenceEstimators: Computational Causal Inference for Applied Researchers
Fernandez, MAL
, Zivich, P and Smith, MJ
(2020).
migariane/TutorialCausalInferenceEstimators: Computational Causal Inference for Applied Researchers.
[Dataset].
Zenodo.
https://doi.org/10.5281/zenodo.4424912
, Zivich, P and Smith, MJ
(2020).
migariane/TutorialCausalInferenceEstimators: Computational Causal Inference for Applied Researchers.
[Dataset].
Zenodo.
https://doi.org/10.5281/zenodo.4424912
This repository makes available to the scientific community the data and code used in the manuscript "Tutorial: Introduction to computational causal inference for applied researchers and epidemiologists using reproducible Stata code with translations to R and Python".
Alternative Title
Tutorial: Introduction to computational causal inference for applied researchers and epidemiologists
Keywords
Causal Inference, Regression adjustment, G-methods, G-formula, Propensity score, Inverse probability weighting, Double-robust methods, Machine learning, Targeted maximum likelihood estimation, Epidemiology, Statistics, Tutorial| Item Type | Dataset |
|---|---|
| Capture method | Simulation |
| Date | 15 December 2020 |
| Language(s) of written materials | English |
| Creator(s) |
Fernandez, MAL, Zivich, P and Smith, MJ
|
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Date Deposited | 06 Jan 2021 10:02 |
| Last Modified | 29 Sep 2021 16:00 |
| Publisher | Zenodo |
No files available. Please consult associated links.
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