Questions tagged [causality]

The relationship between cause and effect.

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46 views

how to measure the causal impact of interventions which happen at different times on different time series?

My data consists of a bunch of time series of daily clicks on some merchandises on a website, a portion of which have an intervention (only 1 intervention per time series), others don't. The ...
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1answer
69 views

Does convergent cross-mapping require you to control for other variables?

There's a really cool method called convergent cross-mapping (Tsonis et al. (2018)) that's used to see if two time-series are causally linked within a dynamic system. It seems really powerful and like ...
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1answer
109 views

Causal Inference After Feature Selection

I am interested in this forum's thoughts concerning the use of LASSO for feature selection in a high dimensional dataset and subsequent OLS regression to adjust for confounding on the most frequently ...
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1answer
48 views

How to apply structural equation model (SEM) to set up the SNP pleiotropic effect

Some researchers will use SEM model to detect pleiotropic effect and causal effect. In my opinion, SEM model can not be considered as the proof for effects, instead, the SEM model only provides the ...
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Inconsistent assumptions about instrumental variable

In the linear regression model $Y= X\beta+u$ , when $X$ is endogenous , the OLS estimator will be biased. If we can find an instrumental variable $Z$ which is correlated with $X$, but uncorrelated ...
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1answer
28 views

Infer one link of a causal structure, from observations

Suppose I have continuous random variables $X,Y,Z$ with the following causal structure:                                                        I hypothesize a simple regression model for each r.v., ...
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57 views

Can we use Bootstrap to estimate MSE?

The classic problem in causality is that we do not observe the ground truth--the actual treatment effect. Let's say I have several methods in my toolkit (CART, causal tree, causal forest, BART etc.) ...
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How do you explain the condition under which a simple OLS regression model can be used to yield the causal effect of a treatment? [duplicate]

So, this is a question from an econometric tutorial and I am simply confused (and nervous) about this question. Is an assumption the same as a condition? What kind of example can I give that best ...
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1answer
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How would econometricians answer the objections and recommendations raised by Chen and Pearl (2013)?

In their article, Chen and Pearl (2013), critically examined 6 econometric textbooks, among these the textbooks written by Wooldridge (2009) {the introductory book}, and Stock & Watson (2011). ...
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1answer
38 views

How to regularize only some features in a logistic regression, using Python? [closed]

Say I want to fit the following logistic regression model: $E(y)=(1+e^{-f(X)})^{-1}$ where $f(X) = \beta_0+\beta_1^TX_1 +\beta_2^TX_2 $ and I want to add L1/L2 regularization on $\beta_1$ vector but ...
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Control for common factors

Hi I have a question about how to control for common factors. I used people of a state as the sample to investigate a causal relation between two variables, y and x. Although there are a lot of ...
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Counterfactual inference using functional causal model (Example from Koller-Friedman)

I'm currently studying Chapter 21 Causality from the book Probabilistic Graphical Models (Koller, Friedman). I'm struggling to understand how the values in the joint posterior have been obtained in ...
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1answer
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OLS Regression > Reverse Causation

I am interested to examine the effect on consumption on marijuana with the implementation of tax. I will be examining it on 51 states in US including DC, over 6 years. The other controlled variables ...
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1answer
122 views

Are model diagnostics necessary for linear model run on matched data?

On https://cran.r-project.org/web/packages/cem/vignettes/cem.pdf, it mentions that "Using the output from cem, we can estimate SATT via the att function. The simplest approach requires a weighted ...
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1answer
47 views

Directionality of Mediation Effect

Is it possible to (statistically) determine the directionality of a mediation effect, i.e. $X \rightarrow M \rightarrow Y$ vs. $X \rightarrow Y \rightarrow M$ for example, or is this purely based on ...
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Standard errors propensity score matching

I am currently working on a causal inference project via several panel regression specifications, and one of the methods I'm using to obtain more robust results is propensity score matching (PSM). For ...
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1answer
438 views

Do I need to adjust OLS standard errors after matching?

Suppose I use propensity score matching to create a dataset of treatment and control observations. Then I run OLS regression with some covariates that were not necessarily included in the propensity ...
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Sample Inclusion Criteria for an Intent-To-Treat Analysis in an Encouragement Design With One-Sided Non-Compliance

This question is about how to define the sample in an Intent-To-Treat analysis of an experiment with balanced pre-assignment and an encouragement design. This is a bit different than the usual setting ...
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1answer
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Invariance of average output given output maximization

Assume that here are two areas $a = {1,2}$ and that $(e_{i1},e_{i2})$ is IID Gumbel location 0 scale 1 for all $i$. Assume further that $$w_{i1} = \mu_1 + e_{i1} \\ w_{i2} = \mu_2 + e_{i2}$$ and that ...
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2answers
161 views

causal impact estimation

say i have following causal model: outcome variable: Y (e.g. sales) treatment variable: T (e.g. price) covariate variable: x2 (e.g. traffic) unobserved variables: U (unobserved) causal relation: ...
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3answers
289 views

How to calculate causal effects with repeated exogenous shocks over a time series

A rather frequent problem in causal inference is that we come across various shocks over time and try to measure their impact. In the case of a single shock we can use bayesian methods to predict how ...
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272 views

Avoiding adjustments for time-varying controls in difference-in-differences (DID)?

In difference-in-differences (DID) analysis, it seems like a "folk theorem" that one should be very wary of adjusting for time-varying controls. The reason, eminently plausible, is that ...
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1answer
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Examplary applications of Pearl's theory of causality

Causal theories described in Pearl (2009) seemingly find more and more attention in methodological papers (Elwert and Winship, 2014; Pearl, Glymour and Jewell, 2016; Lewbel, 2019; Imbens, 2019). But ...
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1answer
61 views

Causal Inference on test scores

I administered a test and wanted to know if the exam scores were influenced by watching videos. The participants were randomly entered into 2 arms. I have one control arm that did not watch videos, ...
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0answers
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Imposing a distribution on a dependent variable to increase variation in the dependent variable - disaggregating data

The question I have essentially has to do with dis-aggregating data, based on a known distribution of the data with respect to a certain variable. It has some resemblances with post-stratification, ...
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3answers
901 views

Can I make recommendations using inferences from multiple linear regression?

I have a question that doesn't seem to fall into classic "recommender systems", but may fall into the category of causal inference (though I'm not sure). Say I have dataset of sales for a ...
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How to calculate the probability of a non-independent / autocorrelated event with a cross-section

Adjusting a probability curve is one of the main uses of machine learning today given its high flexibility. The problem is that they are often used not optimally due to their excess flexibility. An ...
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Causal modelling: specifying model additively or hierarchically?

Let's assume we would like to examine regional disparities in income. We are NOT interested in country-wide effects. A DAG tells us to adjust for age and education. DAGs do not tell anything about ...
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1answer
278 views

What can be done when a covariate was influenced by the experimental treatment?

I have a problem regarding my data for an ANCOVA. I conducted an experiment with a 2x2 between subjects design (4 different treatment groups) and covariates. Due to the treatment I was just able to ...
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1answer
44 views

Front door formula - calculation in practice

I am reading about the front door criterion and I want to make sure that I understand what is calculated in the second part of the formula, where the backdoor path between $Z$ and $Y$ is blocked by ...
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2answers
445 views

Heterogeneous Treatment Effects with Continuous Treatment (e.g. using BART)

Overview: Most of the causal inference literature (both theoretical and applied), I have seen on heterogeneous treatment effects, only considers the case with a binary treatment $T\in\{0,1\}$. However,...
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How to use causality knowledge to improve linear regression? [closed]

As Peter mentioned in this reply https://stats.stackexchange.com/a/26412/152503 Sometimes we do have a priori information about the causality relationship between features/predictors Using the fire ...
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Sequential Causal Inference Scenario

I am working on a problem where I am trying to estimate the effect of whether event C will occur given the time to B. The following scenarios illustrate the possible paths my system may take. A -> ...
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3answers
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Representing interaction effects in directed acyclic graphs

Directed acyclic graphs (DAGs; e.g., Greenland, et al, 1999) are a part of a formalism of causal inference from the counterfactual interpretation of causality camp. In these graphs the presence of an ...
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5answers
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Is it appropriate to use “time” as a causal variable in a DAG?

This question might be better suited for philosophy.SE, but I will post it here in the first instance, since it involves technical aspects that are best understood by users on this site. The title ...
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1answer
43 views

Why is ANCOVA not appropriate for modelling post-intervention outcome, controlling for baseline

I was trying to understand the different use-cases for differences-in-differences models vs. ANCOVA (post-period = pre-period + experiment_group), for observational data. I came across the below ...
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0answers
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How to implement Judea Pearl's SCM model? [closed]

How could I implement Structural Causal Model (SCM) in R/STATA/SPSS? I've read the first few chapters of Pearl's Causality and was fascinated by his SCM approach for causal inference. And here is my ...
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1answer
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Carrying Out Interventions Based on ML “Feature Importances”

Recently, I have been studying causal inference and have come to a bit of a crossroads with respect to making decisions based on the analysis of data (especially in a business/industry setting). ...
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0answers
63 views

How to write a triple differences model with fixed effects?

I have a bunch of states $i$ Some are treatment states and others are control states, where $T_i$ is 1 if treatment I believe the treatment effect differs for big states, where $B_i$ indicates if a ...
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1answer
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Difference in difference - everyone treated and measure different response?

I was wondering if there is a model or study where everyone receives the treatment and measures how post-treatment outcome is different. For instance, in a state, minimum wage rose and estimate ...
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2answers
592 views

Under what conditions does correlation imply proximity to causation?

I've recently had an experience with the whole "correlation does not imply causation", which is certainly true as far as a true/false proposition is concerned, but which also seems to be ...
4
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1answer
251 views

Calculate single absolute standardized difference across levels of a categorical treatment variable cobalt::bal.tab

Can I calculate a single absolute standardized difference (ASD) across the levels of my categorical treatment variable? For reporting in a balance table. I performed an inverse probability of ...
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17answers
62k views

Under what conditions does correlation imply causation?

We all know the mantra "correlation does not imply causation" which is drummed into all first year statistics students. There are some nice examples here to illustrate the idea. But sometimes ...
6
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1answer
412 views

Difference Omitted Variable Bias and Confounding?

Is there a difference between omitted variable bias and confounding bias in linear models? To my knowledge, when investigating the causal effect of $X$ on $Y$, a confounder is a variable $Z$ that is ...
3
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1answer
50 views

Is there any precedence for using time for both differences in difference-in-difference analysis?

The textbook example of a difference-in-difference regression uses time at the first difference (pre- vs. post-intervention) and geographical area as the second difference (location where intervention ...
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How conditioning happens?

F. Elwert and C. Winship in the paper "Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable" (content available here) discuss conditioning on different types of ...
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3answers
3k views

How can I compute the standard error of the Wald estimator?

According to Cameron and Trivedi Microeconometrics 2006, page 98-99, the Wald estimator can be written : $$ \widehat{\beta}_{Wald} = \frac{(\bar{y_1} - \bar{y_0})}{(\bar{x_1} - \bar{x_0})} $$ with :...
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0answers
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Causal assumptions when treating time series as a bunch of points

Suppose there are two time series, $x_t$ and $y_t$, that capture daily counts of some sort. $x_t$ is believed to have causal impact on $y_t$. Suppose further that a simple regression is fit to the ...

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