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Questions tagged [causality]

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.

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constructing an expertise based bayesian network in causalnex

Up to now, in causalnex package, I only encountered Bayesian networks that were constucted from data. I want to know how to create my own network with my node parameters and CPDs from expertise. Anybody has some reference to it or an example?
User666x
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Stats: Short Way to Find Pairs in a Set That Have Correlation Between Them

This is a general statistics question. Let's say I have a set consisting of several time series and I would like to find pairs that have correlation. Is the only way to do that is to compare each pair one by one? It does not seem so convenient since…
Harun Türkmen
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ARIMAX exogenous variables reverse causality

I try to fit an ARIMAX model to figure out whether the containment measures (using the Government response stringency index, numbers from 0 to 100) are having a significant effect on the daily new cases rate. I also want to add test rates. I…
Wurzelqueen
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Granger's MaxLag

I have a developer who has created a python script to determine the granger's causality of several datasets that are approximately 3 years worth of daily data (approx 1100 data points for each time series). The script seems to run well but we are…
trauch
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Using bartCause package to predict uplift

I'm trying to use the bartCause package to build an uplift model in R. Unfortunately I have trouble to integrate the data frame in the right way - error message: $<-.data.frame`(`*tmp*`, "lift", value = c(0.159231848781688, : replacement has 160…
Marcel
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Loop Causal Impact in R over multiple datasets and automatically export results

I need some suggestions on how to solve this problem. I have a number of zoo objects on which I want to perform a Causal Impact analysis in R, using the homonym package developed by Google. To automatize the process, I want to run a loop over the…
Giant Steps
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Causal Inference in observational data

I am using the python package DoWhy to see if I have a causal relationship between tenure and churn based on this site. # TREATMENT = TENURE causal_df = df.causal.do('tenure', method = 'weighting', …
James Taylor
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Performe qnorm() for p-values of 0 and 1

I'm doing a meta-regression-analysis for Granger non-causality tests in my Master thesis. The effects of interest are F- and chi-square distributed, so to use theme in a meta-regression they must be converted to normal variates. Right now, I'm using…
BongoKing
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How to use covariates in rddtools rdd_reg_lm function?

I am trying to run a parametric RD regression using the rddtools R package. However, the package documentation is not very clear to me. First: the function to define an RD object is: rdd_data(y, x, covar, cutpoint, z, labels, data) where covar, in…
José Eduardo Sousa
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How to evaluate a call to match.call()?

I'm trying to use a few functions of an R library called "causaldrf". Let's say, inside the library, we have a function "func(a,b)" that takes a string "a" and calls a column named "a" in a dataframe "b". The function is implemented like this…
user2734371
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Is it possible to use "and", "or" "not" as relation/predicate in an ontology? In order to represent causality?

If we use an ontology we can represent many things using semantic triple. I was wondering how can I represent this: A and B cause C or A or B cause C ? I don't want to do reasoning, I only want to represent. Is it possible to use and, or,…
blackzeitoun
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Causal inference - IPTW vs nearest neighbour matching

I am doing a quasi experimentation and am interested in getting ATT. i have a data with 260k entries where Ti = 0 and 5k entries where Ti = 1. I am calculating ATT with iptw technique where I achieve a great balance and the treatment effect -on…
Vishal Gupta
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Rolling Granger Causality Test

I'm trying to use the rollapply function from the zoo package to estimate Granger causality with a rolling window, the grangertest function is from the package lmtest, I have monthly data span over the period 1976-1984. y y1 Jan…
Ameer
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Causal Impact package: Calculate posterior tail-area probability from model estimates

I am currently using the CausalImpact package for some research and in this context I need to know and be able to explain, how the posterior tail-area probability is calculated in order to reproduce that value for validation purposes. Does anyone…
Tiko
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Causality map changing when order of the variables are changed

I am using bnlearn and pcalg R packages to obtain the causality map from the datasets. There is an order-independent algorithm which claims to be independent of variables are given as input. When I change the order the variables, directions of…
Artiga
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