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Questions tagged [causal-diagram]

Graphical methods for investigating causality, the related [confounder] tag, do-calculus, interventions, and counterfactuals.

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Pearl intervention formula?

Given the causal graph $(Z\to X$, $Z\to Y$, $X\to Y)$, according to Pearl’s intervention, the effect of intervening $X$ on $Y$ can be estimated as $$P(Y=y|\operatorname{do}(X=x)) = \sum_z P(Y=y|X=x,Z=...
Diep Luong's user avatar
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Moderated Mediation in a "Two-Step" Structural Equation Model

Can someone please help me figure out how to include a moderator in the structural equation model (SEM) below? It's a "two-step" model in the sense that there are two causal linkages, one ...
JalapenoSupremacy's user avatar
2 votes
1 answer
32 views

When the direction of causation can plausiblely run in either direction, is there a good stat approach to distinguishing relative strength?

I am interested in an instance where it is plausible that ideology influences economic outcome, and also that economic outcomes influence ideology. Assuming that I have good and relavent measures of ...
andrewH's user avatar
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3 votes
1 answer
64 views

Causal variables and causal independence of the noise variables

In causality, my understanding is that, if we have causal variables $S_i$, we must have / assume that the (exogenous?) noise variables associated with each $S_i$ are causally independent of each other....
The Pointer's user avatar
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multiple Mediated moderation

I am trying to determine if this model represents mediated moderation or moderated mediation and why. I have attached a visual representation of the path diagram for $Y_1=\beta_0 +\beta_{X1}X_1+\beta_{...
JewJitsu11B's user avatar
4 votes
1 answer
64 views

causal effect and exogeneity in small samples vs in large samples

Under this title two questions are included. In regression of Y on X and controls Z with random error e, In small sample if strictly exogeneity, i.e. E(e|X,Z)=0, is satisfied, does it means the ...
jerry's user avatar
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2 votes
1 answer
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Interpretation of estimates for adjusted variables

I've started using DAG to improve the construction of my regression models and I was wondering if it made any sense to interpret the estimates I get for variable I adjusted for in my model ? Let's say ...
Boussens-Dumon Grégoire's user avatar
1 vote
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27 views

What causal inference method is suitable to identify the effect of different components of a webpage on the decision to purchase?

I am getting started with causal inference for a project where I want to evaluate the causal effect of different components of a webpage on users' decision to purchase. For illustration purposes, let'...
gummy's user avatar
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5 votes
2 answers
182 views

How to determine if a directed edge is visible? What does visibility tell us?

Both of the above PAGs (Partial Ancestral Graph) are generated using the FCI (Fast Causal Inference) algorithm under identical conditions, the only difference being that the one on the right is ...
ColorStatistics's user avatar
3 votes
1 answer
33 views

Understanding how to evaluate the integral causal-effect expression

I have this expression $$ p( Y \mid \text{do}(Z=z)) = \int_{B, S, W, X} dBdSdWdX \ \ P(B | S) P(W | B, S) P(X | B, S, Z=z) \left[ \int_{Z'} dZ' P(Z'| B,S,W) P(Y | B, S, W, X, Z') P(S) \right] $$ ...
Astrid's user avatar
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Causal additive intervention operation

I am reading the following paper by Shpitser and Pearl: Effects of Treatment on the Treated: Identification and Generalization. On page 517 they provide a corollary concerning the additive ...
wrong_path's user avatar
1 vote
1 answer
28 views

Causal Loop Diagrams vs. Structured Causal Models

What's the difference between causal loop diagrams (CLDs) and structured causal models? I know that Pearl's Structured Causal Models (SCMs) are directed acyclic graphs (DAGs). However, it seems that ...
phylosopher's user avatar
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0 answers
12 views

Inducing Paths Definition Ambiguity

I am relatively new to the causal discovery space and I have a clarifying question regarding the definition of an inducing path. In Causation, Prediction and Search (page 173), the authors state that ...
nothingNew's user avatar
3 votes
1 answer
47 views

Deriving conditional independence statements for causal graphs with selection nodes

In "basic" causal graphs / DAGs / probabilistic graphical models (PGMs), conditional independence statements can be derived using the d-separation criterion. How does this work if selection ...
Eike P.'s user avatar
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How to make nonlinear predictions on categorical treatments in causal inferece given causal graph?

0 I was learning causal inference and discovery these days and have suffered from this question for a long time. From my understanding of the literature, It seems causal inference is quite different ...
Wenyao Leo's user avatar
5 votes
2 answers
278 views

Why does controlling for a collider open a path, while controlling for a confounder closes a path, if there are relations to third variable for both?

Collider bias occurs when there is no association between X and Y but when a third variable which is caused by both X and Y is controlled for, this "opens a path" between X and Y and leads ...
JElder's user avatar
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18 votes
3 answers
866 views

Causal diagrams necessary in randomized controlled trials?

I understand how a properly administered RCT rules out confounders because there are no variables influencing the treatment/control group assignment except randomization (meaning no backdoor paths ...
RobertF's user avatar
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1 vote
1 answer
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PC algorithm in "Causation, Prediction, and Search"

In the page 120 in "Causation, Prediction, and Search", why the edge B-D will not be removed if the edge E-D is mistakenly removed from the initial complete graph. I think B-D is D-connected ...
Nick's user avatar
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14 votes
2 answers
352 views

What is the stopping criterion for adding nodes to a causal DAG?

I'm currently involved in creating a causal DAG (Directed Acyclic Graph) to map causal relationships of a real industry problem. The more I think, the more ancestor nodes I add to the DAG which is ...
Matheus Torquato's user avatar
2 votes
0 answers
24 views

Overfitting if estimating multiple target parameters in dataset (avoiding Table 2 Fallacy)?

For my job I'm sometimes asked to find the driving factors behind a healthcare outcome such as total annual cost or # of inpatient visits. "Driving factors" typically means reporting average ...
RobertF's user avatar
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12 votes
3 answers
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Are directed acyclic graphs (DAGs) only used for visualization?

I see people using these DAGs a lot in articles (e.g. this vignette). Are these kinds graphs only serving purposes of aesthetics and visualizations representations? Or do these graphs actually have ...
stats_noob's user avatar
4 votes
1 answer
66 views

What is an intuitive explanation for a lay-person why controlling for a collider is bad practice while controlling for a confounder is good practice?

Cinelli et al., 2022 and Wysnocki et al., 2022 describe in technical terms how controlling for a collider can lead to biased estimates. If one needs to explain why one should not control for a ...
JElder's user avatar
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How can we estimate the combined causal effect of two separate parents in a Bayesian network?

Consider the following partially-defined Bayesian network: We know the probability of C given A is True and B is False We know the probability of C given A is False and B is True We know that C can ...
Henry Howard's user avatar
1 vote
0 answers
76 views

A question about "do" operator under unobservable confounder

The original question is here. Suppose we have a DAG in the figure. If there is no confounder $U$, as chang_trenton point out since $S$ and $W$ happen before $X$, we have $$ P(Y \mid do(X), S) = ...
香结丁's user avatar
  • 203
1 vote
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Do operator in a given DAG

The Original question is here Suppose we have a DAG in the figure. The question to is find the decomposition for $P(Y \mid do(X), S)$. If the backdoor criteria can be applied here, then the following ...
HAHAHA's user avatar
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4 votes
1 answer
103 views

A question about do calculus

Suppose we have a DAG in the figure. I want to find the formula for $P(Y \mid do(X), S)$. What I think is that: Since $W$ is the parent of $X$ then we should have $$ P(Y \mid do(X), S) = \sum_{W} ...
香结丁's user avatar
  • 203
1 vote
0 answers
28 views

Is survey participation a cause of survey response?

I am rewatching Statistical Rethinking 2023 - 11 - Ordered Categories because McElreath mentions some causal assumptions about survey responses, which I am interested in. He proposes a causal diagram ...
Galen's user avatar
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2 votes
1 answer
126 views

Constructing a structural equation model/causal graph

I would like to understand some intuitions behind the following causal graph/SCM. Where as $X_1, X_2$ are expenditure on promotional activities. My main interest lies in understanding the fact that ...
jack's user avatar
  • 55
1 vote
0 answers
71 views

Multiple covariates as treatment in double ML

I have multiple economic indicators as covariates such as employment rate, gdp growth, average wage, etc. I want to estimate each of them's effect on travel demand. I was thinking of two steps: Make ...
tomtomxu's user avatar
4 votes
2 answers
211 views

Variable selection with a theoretical DAG vs algorithmically discovered DAG

I'm analysing data from an electronic health record and determining what variables to include in a model to close back doors and omit bias. I've read that it is important to have a subject specific ...
Geoff's user avatar
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2 votes
1 answer
79 views

Why is d-separation only for disjoint sets?

I'm reading Molak's Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more and I made note that I've taken the ...
Galen's user avatar
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2 votes
0 answers
48 views

Causal discovery on partially known causal DAG

Often in data science, we have partial knowledge of the causal DAG structure. Regarding some of the possible edges in the DAG, we are in doubt. Are there any resources to tackle this setting? The ...
Anirban Chakraborty's user avatar
4 votes
2 answers
596 views

Isn't strong ignorability an incorrect assumption in complex causal structures?

I have seen that in many papers/competitions for causal inference, the assumption of strong ignorability is made - $P(Y^{x}\perp X\mid V)$, where $X$ is the treatment, $Y$ the outcome and $V$ ...
Anirban Chakraborty's user avatar
3 votes
1 answer
109 views

Causal inference in DAGs and resulting structural equations

I am trying to understand the difference between the two modelling approaches described below that stems from the causal graphs. Our goal is to causally measure the total treatment effect of our ...
jack's user avatar
  • 55
2 votes
0 answers
17 views

Can my cycle-cut algorithm sample any DAG?

I am doing some computational simulations to validate a procedure involving structural equation models and causal inference. I wanted to sample from the possible space of DAGs on $n$ vertices. I can ...
Galen's user avatar
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1 vote
0 answers
54 views

How do I interpret the identification step logs in Causal Inference using DoWhy? [closed]

I am running Causal Inference to determine whether the mass of a vehicle affects the Co2 emissions. I understand that DoWhy follows a particular structure that is modeling-> identification -> ...
Vahid Nesro's user avatar
1 vote
0 answers
17 views

Difference between query and distribution in causal inference

Reading the causality literature, we see the concepts of "interventional" and "counterfactual" query as well as "interventional" and "counterfactual" ...
CausalQuestions's user avatar
3 votes
1 answer
165 views

Selection of Competing Exposures in a DAG: How many to use?

I am trying to get my head around when and how to include Competing Exposures in DAGs. In my searching I keep finding statements that are very similar to the quote from the dagitty tutorials - "...
jnat's user avatar
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0 votes
1 answer
53 views

Causal Inference in a Multivariate Equation

I am wondering if both the coefficients can be identified in a causal sense given the context and the resulting multiple regression equation. Imagine a scenario where we have two investment ...
max's user avatar
  • 65
6 votes
1 answer
306 views

Causal inference and the backdoor-criterion

I am trying to determine if the authors of the following report missed out on an important factor or if i am the one who have missed out on something. In the following report: Bias Correction For Paid ...
max's user avatar
  • 65
3 votes
1 answer
45 views

Testing for conditional independence with nonlinear relationships

I am reading about the IC and IC* (Inductive Causation) algorithms for discovering DAGs from observations. The first step of the algorithm is for each pair of variables a and b, search for a set of ...
Marc Bacvanski's user avatar
1 vote
0 answers
55 views

Path tracing rules for nonlinear relationships

I'm learning about Wright's path-tracing rules, and because they deal with covariances it seems like they make the assumption that relationships between variables are linear. If we have nonlinear ...
Marc Bacvanski's user avatar
1 vote
0 answers
14 views

In a causal diagram where the change score $\Delta Y=Y_1-Y_0$, does $Y_1$ cause $\Delta Y$ or does $\Delta Y$ cause $Y_1$?

In Shahar & Shahar (2010), the authors argue that in a typical pre/post observational study on two longitudinal outcomes $Y_0$ and $Y_1$: the change score $\Delta Y=Y_1-Y_0$ causes the post-...
RobertF's user avatar
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4 votes
1 answer
104 views

Covariate adjustment for "mediated" reverse causality

I have made the following DAG in dagitty.net: DAGitty says "The total effect cannot be estimated by covariate adjustment". I don't understand why I can't close the backdoor path by ...
robertspierre's user avatar
3 votes
0 answers
23 views

Competitions/datasets fit for exploring Pearl's graphical causal models

Are there any competitions/challenges/datasets fit for testing Pearl's graphical causal inference methods? I do not necessarily mean live competitions. I would expect these setups to be different than ...
Anirban Chakraborty's user avatar
1 vote
1 answer
72 views

How can you rewrite the estimand in terms of propensity scores? Dowhy question

I am going through the backdoor criterion and how we get from an expression involving do to one which doesn't as below. What i don't quite get is how to rewrite this estimand in terms of propensity ...
Maths12's user avatar
  • 579
2 votes
2 answers
469 views

DAG - why is the path open?

I have this DAG As I understand it, the paths D <- Ed -> St -> P -> Su and D <- A -> P -> Su are both closed because the contain the collider P. If I condition on P, both these ...
user654345678's user avatar
3 votes
1 answer
92 views

How to understand the second rule of front door criterion?

In the Definition 3.4.1 of Pearl's causal inference book (Primer), the second rule for the front door criterion is "There is no backdoor path from $X$ to $Z$". But from my understanding, ...
bcxiao's user avatar
  • 33
2 votes
2 answers
167 views

Can controlling for a variable block the backdoor path opened by controlling for a collider?

I have made the following model in DAGitty: Where X2 is controlled for. DAGitty says: The total effect cannot be estimated due to adjustment for an intermediate or a descendant of an intermediate. ...
robertspierre's user avatar
0 votes
2 answers
258 views

Causal counterfactual inference model comparison

When refuting two causal models, model 1 has a bigger p-value and an estimated effect closer to the new effect (compared to model 2). Both can't be refuted because they have a p-value above 0.05. Is ...
Rui Lima's user avatar