# Questions tagged [causality]

The relationship between cause and effect.

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9 views

### Causality comes form experiment manipulation or statistical calculation?

It is known that "Regression can only imply correlation but not causality" But whether a research can draw their variables to causality relationship is somewhat determined by whether the ...
14 views

### Adding baseline covariates in stabilized weights change covariate balancing

I am computing weights using inverse probability of treatment weighting for marginal structural models (Robins et al. 2000). With both time-varying and time-invariant (baseline) covariates, some ...
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### Invariance of causal prediction

I am reading Causal inference by using invariant prediction: identification and confidence intervals by Jonas Peters (link to the resource is here: https://rss.onlinelibrary.wiley.com/doi/full/10.1111/...
1k views

### How does Inverse weighted propensity score regression differ from propensity score matching?

I understand that in inverse weighted propensity score regression, a set of weights are used to create scoring. In propensity score matching, a propensity score is created for each strata and people ...
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### How is the log likelihood calculated for bayesian networks?

In structure learning, there are score-based methods which rely on information criteria such as BIC or AIC. BIC, specifically, is defined as: $$BIC = k \ln(n) - 2\ln\left(\hat{L}\right)$$ Where $k$ ...
379 views

### How to determine if two categorical variables are dependent while controlling for a 3rd categorical?

I have 3 categorical variables: country, gender, and liked (whether the user liked the content or not). Using Chi-squared I see that 'liked' is dependent on country, that 'liked' is dependent on ...
20 views

### What is the correct way to calculate the covariate-specific effect in causal inference?

My question is related to the concept named "Covariate-Specific Effects" in the book "Causal Inference in Statistics: A Primer". In Section 3.3, it is called the "w-specific ...
348 views

### How to interpret Pearl's do notation?

I'm going through the Dragonnet paper (slides available here), and the authors use Pearl's do notation to make this claim: How can I interpret the do notation? Is the author claiming that the average ...
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### Simpson's paradox in Judea Pearl's book?

I'm looking at the following question in Judea Pearl's primer on causality In an attempt to estimate the effectiveness of a new drug, a randomized experiment is conducted. In all, 50% of the patients ...
33 views

### Regression for Completely Randomized Experiments

I'm reading Guido W. Imbens and Donald B. Rubin's book on Causal Inference. In chapter 7 they try to justify using a regression model to estimate the mean casual effect in a completely random ...
30 views

### Fixed effects in DAGs

Let's imagine I'm interested in studying the causal effect of beliefs in some ideas and behavior related to these ideas (say, if I believe sunscreen is good for my health, I use more sunscreen etc.). ...
480 views

### Can I use Rolling and Window cross-validation techniques to check feature importance and forecasting error stability?

I want to propose a simple experiment. Let's say I have a time series data, where I first split data into train and test sets and then work with my training set to pick the best model to do forecast ...
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### How to test for a partially mediated model?

I have a dataset with three variables: Outcome, Exposure, and Mediator. My hypothesis is that the variables are related as in the following DAG: In particular I want to test that "Mediator" ...
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### Difference between total causal effect and average treatment effect

I'm new to causality and have a basic understanding of Average Treatment Effect (ATE). Recently, I came across Judea Pearl's definition of Total Effect/Total Causal Effect. Could anyone tell me what ...
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### What can we explain while adding region*year fixed effects, the sign flip?

In my work, I used OLS model to run the regressors on Return on Equity.And the result is as below While variable of interest is pt, which is post*treatment in difference-in-difference setting. While ...
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### Constrastive vs Counterfactual Explanations

Is there any canonical definition for Contrastive vs Counterfactual explanations? In the literature, I keep reading different versions but I wonder if there are good definitions or illustrative ...
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### All-subsets regression and parameter shift to estimate or identify omitted variable biases?

I have multiple ($12$) predictors ($X$) for an outcome (spending) where it's likely/possible that: Some predictors are correlated Some predictors could (partially) mediate the effect of others There ...
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### What are the main methods for estimating the Average Treatment Effect in Observational Studies outside of matching?

I am wondering what the main methods for estimating the Average Treatment Effect in Observational Studies are outside of matching. In matching, there are weighting, stratification, propensity score ...
69 views

### Testing pre-trend in DID

I follow Dasgupta, 2019 to set up the control and treatment variables for staggered implementation of laws among countries as events. The treatment and control groups are explained in one topic. I am ...
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### Can this additional data improve the validity of Difference-in-Differences estimate

I am aiming to measure the impact of a treatment (a marketing stimulus) on product revenue. The data has resulted from a natural experiment. The set-up is tabulated below. Cells in the table indicate ...
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### Omitted variable bias: which predictors do I need to include, and why?

For a last couple of weeks I've been thinking about OVB (Omitted variable bias) in the context of regression and solution for that (how to avoid this problem). I am acquainted with Shalizi's lectures (...
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### How are prerequisites/eligibility criteria defined in causal contexts?

In a causal graph (DAG), $A\to B$ means $A$ causes $B.$ Even correlation can be defined with causal relationships (for example, maybe $A$ is correlated with $B$ because $C$ causes both $A$ and $B$). ...
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### When should use the word “causation” versus “causality”?

Today, I read a couple of discussions in Cross Validated, and these two words popped up quite a bit. I do not know how to differentiate them in usage (especially writing) because they are quite ...
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### Visualizing time series regression results in a causal framework

Suppose I have a set of independent variables that I believe to, collectively, cause the observed level and changes in the value of the dependent variable, and I have the results of a regression of ...
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### Causal inference for a trained Gradient Boosting of decision trees

I am quite new to the space, but I was wondering if it was possible to do causal analysis with a model trained with Gradient Boosting of decision trees? I know there are packages like causalnex, https:...
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### causal inference exercise - “covariate-specific effect”

This graph and questions come from: CAUSAL INFERENCE IN STATISTICS A Primer - Pearl Glymour and Jewell (2016). We are interested in the effect of $X$ on $Y$. In order to identify it we looking for the ...
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### Does education level affect salary?

This is an interview question that I came across, and I'm not sure how to answer it. There are two ways of phrasing a causal question: If someone has a high salary, was it because they had a high ...
900 views

### Which OLS assumptions are colliders violating?

The following webpage says that: We should not control for a collider variable! Which OLS assumptions are colliders violating?
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### Difference-in-difference: common trend

I'm new to this concept, and I'm referring to the book Mastering Metrics: The Path from Cause to Effect by Joshua D. Angrist and Jörn-Steffen Pischke. It states that an important assumption of ...
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### Why is randomness so useful?

Where by "why" I do not mean "list of use cases for randomness." If one has a quantitative question Q about topic X, it does not seem intuitive that values that by definition have ...
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### What does counterfactual mean in Difference-in-Difference setting?

In a topic asked, the expert mentioned the word "counterfactual" [W]hy do they need to write down "adopted a leniency law at some later point of time"? Because in Korea case, the ...
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### Size of Complier Group (Instrumental Variables) - Mostly Harmless vs. Abadie Kappa

Focusing solely on the case with a binary endogenous explanatory variable $D$ and binary instrument $Z$ and control variables $X$, Angrist & Pischke 2009 ("Mostly Harmless Econometrics") ...
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### Better methodologies to make causal recommendations from correlated data?

I work as a data scientist at a SAAS company. We have an outcome variable, Y, that we consider "success" for our customers. We have a bunch of additional outcome variables X1, X2, X3 that ...
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### Is there a real example in which a correlation finally leads to the discovery of a non-trivial causal relationship?

More specifically, I am wondering if there is such an example satisfying the following criteria: The example happened after 1888, it would be better to be after 1900—I think few people have the ...
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### Difference between an “Empirical Strategy” and an “Identification Strategy” in econometrics?

What are the substantive differences between these terms, specifically for economists? Are instrumental variables, difference-in-differences, and regression discontinuity designs considered ‘...
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### Is the emmeans R package performing causal inference G-computation?

So I am trying to get an understanding of causal inference and how it differs from the usual contrasts. I regularly use the emmeans package in R, and I am wondering when the function emmeans() ...
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### Does confounding always imply endogeneity?

I'm a bit confused with the definitions regarding causal inference. My question is whether we can call measured confounding an endogeneity problem?
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### Equivalence of Inverse Probability of Treatment Weights and Standardization: Hernan and Robins proof

Hernan and Robins provide a proof for the equivalency of inverse probability weights and standardization for estimating the potential outcome mean that I am struggling to follow (technical point 2.3, ...
25 views

### How to prove positive effect of a variable with regression?

I am simply trying to prove that giving cash assistance to a company effects their related financial items in a good way. I calculated the related item's mean for all companies, it's non negative and ...
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### How to best respond to investigator who wants to study secondary outcome

I'm co-investigator on a clinical trial where the we are studying the effect of an intervention. The study is powered to detect a clinically meaningful change for some primary endpoint. My questions ...
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### Instrumental Variable and “Exclusivity”

In the following DAG: Can I use IV1 as an instrument for exposure? In the this video at 4:26 the teacher explains a principle of "exclusivity" for instrumental variables. Cutoff causes ...
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### Is it complete mediation when my independent variabel has a significant effect on the dependent variable, only after adding the mediator variable?

I am currently working on my masters thesis and I am testing for mediation. For this mediation I am using the Baron and Kenny method. For path c, you need to see if the effect of the X variable (...