Causal inference is a branch of scientific inquiry that seeks to understand the relationship between cause and effect. It involves studying the factors that lead to a particular outcome or event and identifying the causal relationships between them. Causal research is often used in fields such as medicine, psychology, and social sciences to identify the causes of various phenomena and to develop interventions that can effectively address them.
Questions tagged [causality]
136 questions
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sklift inference: how to get probabilities for treatment vs no-treatment?
I am working with sklift to describe what the uplift for a given treatment (in this case marketing discount) is. When training the model, we can get both probabilities, such as:
# model results: conditional probabilities of treatment effect
#…
titu84hh
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Justification for the multiplication step in the proof of the front door adjustment
The proofs of the front-door adjustment that I've read take three steps:
Show P(M|do(X)) is identifiable
Show P(Y|do(M)) is identifiable
Multiply the do-free expressions for P(M|do(X)) and P(y|do(M)) to obtain P(Y|do(X))
where Y,X,M meet the…
Kyle Pena
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Causality Tracking Option in Extended Events Seems To Be AWOL
There used to be a checkbox for causality tracking in Extended Events. I don't see it anymore (SSMS 18.8) nor see anything about when where it would have been removed. Anyone know anything?
James E Carroll Jr
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Can I include covariates outside of the minimally sufficient set in a causal framework that aren't in the causal pathway?
I am applying a causal method to a cohort study analysis on pollutant exposure and disease X. Based on our understanding of the disease, we believe that aging is the only confounder.
From what I understand, age would be the item in our minimally…
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ggdag colouring nodes a specific color
I am currently experimenting with ggdag and I want to color the exposure, the outcome, and the rest of the nodes.
How can I make every node that's not an exposure or outcome the this hex color: #fcba03?
This is my working example code so…
Eisen
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Fast way of solving this iterative matrix equality in Python (with PyTorch)
In one of my neural network implementations I have to solve the following problem:
w = f(v) with Lv = q+Dw, where w, v, q are vectors, D is a matrix and L is a diagonal matrix. This of course seems like a difficult dependency problem, but if we…
seaver
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What is meaning of linear systems in Pearl, Glymour, Jewell
In "Causal Inference in Statistics" by Pearl, Glymour and Jewell page 122:
"In linear systems, where reversal of transitions amounts to negating the signs of their effects, we have the standard additive formula TE=NDE+NIE".
What does linear systems…
Actuary David
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"object not found" error in mediation analysis in R
I am doing mediation analysis in R. My mediator is a binary variable, so model.m is run by glm.
set.seed(2022)
data = data.frame(ID = as.character(seq(1,100,1)),group = seq(1,100,1),
iris[1:100,],day1 = rnorm(100), day2 =…
Dianafreedom
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Grangertest in R
does someone knows what I am doing wrong?
I tried everything I've seen on the internet to perform the Grangertest.
The structure of my data is:
structure(list(Belgium = c(10786, 9902, 11119, 10218, 10454,
11014), Netherlands = c(14929, 13905,…
EvA
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2 answers
Obtaining covariates' estimates in rdrobust package
I am using rdrobust to estimate RDDs and for a submission in a journal the journal demands I report tables with covariates and their estimates. I don't think these should be reported in designs like these and don't really know how informative they…
AntVal
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Returning graph and dataframe object
I have the following code which will return a graph of a DAG:
library(dagitty)
library(ggplot2)
dag <- dagitty( "dag {
Y <- X <- Z1 <- V -> Z2 -> Y
Z1 <- W1 <-> W2 -> Z2
X <- W1 -> Y
X <- W2 -> Y
X [exposure]
Y [outcome]
}")…
Eisen
- 1,697
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Bayesian network for continuous variables
I have search and saw some questions on the matter but without answer (due to the fact that the questions were asked more than 1 year ago, I. hoped something has changed)
I am looking for a library to infer bayesian network from a file of continious…
Yuval David
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Error: period.indices$post.period[1] not greater than period.indices$pre.period[2]
I leave the codes here. I am sure some R-savvy people can help me with this issue.
#Causal Impact
#define pre and post period dates
start = "2018-01-01"
treatment = "2020-10-01"
end = "2021-06-10"
#retrieve…
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1 answer
Is the execution of statements in the following code changed by compiler optimization?
In a recent related question I found that the following code
public static void main(String[] args) {
/*1*/ int x;
/*2*/ boolean found = false;
/*3*/ if (!found)
/*4*/ x = -1;
/*5*/ System.out.println(x);
…
lineage
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Accounting for fixed effects in regression discontinuity (rdrobust package in R)
I'm just starting out with rd designs and have a question about accounting for fixed effects. Say I have a dataframe df with outcome variable y (observed across 100s of districts over several years), running variable x. I wish to account for…
