Use for anything related to Judea Pearl's do calculus, in which a quantity of primary interest is a probability of the form $P(x|\operatorname{do}(y)),$ involving the $\operatorname{do}$ operator. Related topics include the back-door criterion, back-door adjustment formula, front-door adjustment formula.
Questions tagged [do-calculus]
6 questions
3
votes
1 answer
How do I make counterfactual forecasts with do-calculus (Bayesian causality)?
I've been doing a lot of research into Pearl's do-calculus, particularly this paper http://ftp.cs.ucla.edu/pub/stat_ser/r350.pdf. I definitely understand the difference between P(y | x0) and P(y | do(x0)), and why it is important (both…
Sinnombre
- 151
3
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1 answer
Controlling confounders in a causal diagram. Isn't the backdoor criterion sufficient?
In Judea Pearl's The Book of Why we find the following causal diagram:
where $U_1$ and $U_2$ are unobserved variables.
The diagram is accompanied by a comment that ensures that neither the back door criterion nor the front door criterion are…
Jsevillamol
- 4,759
2
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1 answer
On the Derivation of Judea Pearl's Front-Door Adjustment Formula in The Book of Why
I have a number of related questions about the derivation of the front-door adjustment formula as given on page 236. Here is the derivation. I would have typed it up, but the diagrams at the far right would have been a pain to include.
There is a…
Adrian Keister
- 10,272
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How do I carry out do-calculus on a mediator variable?
I have been trying to get my head around using do-calculus in causal inference, and I've run into a little toy problem that's confused me and my classmates.
Imagine you have a DAG for some causal model that is defined by $(X \rightarrow M, M…
0
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Multi-objective Structural Causal Bandits
I am reading the paper "Structural Causal Bandits: Where to intervene?" by Lee & Bareinboim (2018). Here is a link: https://papers.nips.cc/paper_files/paper/2018/file/c0a271bc0ecb776a094786474322cb82-Paper.pdf
I am trying to expand their results to…
mathStudent
- 441
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1 answer
Interventional query without adjustment set
Given the following casual graph, we need to find the formula for $P(y|do(a))$ in terms of observed variables Y, A, W, M.
My attempt is to try different back-door and front-door adjustment sets, however, I don't see any. Most likely, I need to use…
