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Also called Probabilistic Graphical Model, used for statistical models expressed via graphs, causal or not. (Nb, "graph" as in graph theory, *not* as in figure or plot).
2
votes
Accepted
How to understand the second rule of front door criterion?
I can understand your confusion. In the Front-Door Criteria of Definition 3.4.1, the original text for #2 read, "There is no unblocked path from $X$ to $Z$." The book's errata changed that to "There i …
2
votes
Accepted
Spirtes' example of d-separation not leading to independence in a directed cyclic graph with...
Here is my explanation. I believe the author is right. It comes down to this: for a double arrow relationship $W\longleftrightarrow Z,$ neither $W$ nor $Z$ is considered a descendant of the other (unl …
4
votes
Accepted
Effect of treatment on the treated using the graph
Ah, I see you are studying Pearl's Causal Inference in Statistics: A Primer, co-written with Glymour and Jewell. Excellent choice!
Theorem 4.3.2 says that if $\tau$ is
the total effect of $X$ on $Y$, …
1
vote
Accepted
Pearl's Causal Inference In Statistics, equation 3.11 - Calculation of group specific causal...
The $w$-specific causal effect of $X$ on $Y$ is quite distinct from the causal effect of $X$ on $Y.$ The causal effect of $X$ on $Y$ is just $P(y|do(x)).$ The $w$-specific causal effect of $X$ on $Y$ …
3
votes
Accepted
Doubts on a proof about graphical models
Having a collider's vertex observed or measured does not mean that causal information can flow through it. What makes causal information flow through a collider is when you condition on the collider. …
5
votes
1
answer
151
views
Causality: Models, Reasoning, and Inference: Diagram Question
I am self-studying Causality: Models, Reasoning, and Inference, by Judea Pearl, and there is a question I am particularly stumped on. It reads like this:
Problem Statement: Given this fragment of a B …