Dag Articles

Page 1 of 1 (4 articles)

3/21/2024 • EN

Demystifying causal inference estimands: ATE, ATT, and ATU

Explains key causal inference estimands (ATE, ATT, ATU) and how to calculate them using observational data, with a focus on R and the potential outcomes framework.

Causal Inference Dag R statistics Tidyverse

Andrew Heiss

9/7/2021 • EN

Do-calculus adventures! Exploring the three rules of do-calculus in plain language and deriving the backdoor adjustment formula by hand

Explains the three rules of do-calculus in plain language and manually derives the backdoor adjustment formula for causal inference.

Backdoor Adjustment Causal Inference Dag Do Calculus R

Andrew Heiss

12/1/2020 • EN

Generating inverse probability weights for both binary and continuous treatments

A tutorial on using R to calculate inverse probability weights for causal inference with both binary and continuous treatment variables.

Causal Inference Dag Econometrics Inverse Probability Weighting R

Andrew Heiss

2/25/2020 • EN

Ways to close backdoors in DAGs

Explains methods like regression and inverse probability weighting to close confounding backdoors in DAGs for causal inference in observational data.

Causal Inference Dag Observational Data Regression Statistical Methods

Andrew Heiss

Dag Articles

Demystifying causal inference estimands: ATE, ATT, and ATU

Do-calculus adventures! Exploring the three rules of do-calculus in plain language and deriving the backdoor adjustment formula by hand

Generating inverse probability weights for both binary and continuous treatments

Ways to close backdoors in DAGs

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