Questions tagged [causality]

The relationship between cause and effect.

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37 views

Cutoff for conditional independence from inverse covariance

I have several covariates of mixed data types (e.g. continuous and binary). I am trying to determine covariate pairs that are conditionally independent of all the other covariates by checking the ...
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54 views

complex Difference-in-difference formula

I have 5-year sales information from a grocery store in Canada. I want to check whether an event that happened in 2017, affected the effect of the price of a product on its sales. For example, imagine ...
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25 views

Intermittent Electricity Output - Causal Effects

I am working on modeling the electricity output of a single power plant. More specifically, I am trying to compute causal effects of a variable prop on output. My model would look something like this $...
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1answer
66 views

Statistical significance of causal models and cross validation

When tuning causal models (e.g. uplift models) using cross validation, how important is the statistical significance of the measurement (e.g., the difference between group A and B, or Control and ...
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65 views

Elastic Net / Lasso as a solution to multiple comparisons and p-hacking? Inferential/Descriptive stats

I have a very large dataset, and I'm trying to find which variable(s) may describe the truth about a certain variable. I've considered just doing OLS on variables that make logical sense. But I've ...
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155 views

Identifying the correlation between a slope and a level

Throughout this post, I assume at least second moments exist. Consider a heterogeneous linear treatment effect model of the form: $$Y_i = \alpha_i + \beta_i X_i$$ where $\alpha_i, \beta_i$ are ...
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1answer
14 views

Can you determine if a correlation exists independent from outliers without conducting an experiment?

Let's say A correlates with B. But, A is correlated with C, D, E, and F which also correlate with B. Could you determine if A's correlation with B is solely due to the fact that C, D, E, and F ...
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35 views

Causal assumptions behind SVAR with sign-restrictions identification

Which causal assumptions are (explicitly or implicitly) made in identification of a structural vector autoregression (SVAR) model with sign-restrictions (see e.g. Uhlig 2005)? By “causal assumption” ...
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2answers
34 views

When is the conditional mean of potential outcomes linear in the propensity score?

Consider an outcome $Y$, treatment $D$, and set of covariates $X$. The outcome is real-valued, the treatment has support $\{0,1\}$, and the set of covariates is a collection of binary variables with ...
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1answer
109 views

Comparing time series data with multiple pairs of time series, or difference-in-difference with continuous treatment conditions?

My dataset contains time-series for two variables ($X$ and $Y$) from 2017 to 2020, for each of many different countries. Each country has its own time series for each variable (X_usa, X_india, Y_usa, ...
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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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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
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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61 views

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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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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19 views

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
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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1answer
24 views

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
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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15 views

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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103 views

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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33 views

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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1answer
98 views

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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3answers
351 views

Monty Hall problem and causality

The Monty Hall paradox is well known, even in this site there are several discussion about it (for example: How can I apply Monty Hall problem correctly? ; Monty hall problem, getting different ...
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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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20 views

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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3answers
903 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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17 views

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
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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55 views

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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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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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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84 views

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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28 views

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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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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57 views

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
43 views

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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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
255 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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1answer
416 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 ...
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1answer
16 views

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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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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60 views

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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82 views

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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27 views

Which techniques can be used to explore causality in repeated cross-sectional data?

I have repeated cross-sectional data for certain variables during 51 years (hundreds of variables, measured every year). The number of samples (individuals) for which these variables are measured in ...
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29 views

Uplift modeling and statistical significance

Is statistical significance in the difference between a control and treatment groups (aka Uplift) needed when training an uplift model? If I have a historical test where no statistical significance ...
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21 views

How to find the [marginal] effect of X on Y when Y is binary and very rare. Can I make groups of similar X and model counts of Y instead?

tl;dr How to model the causal impact of X on binary Y when Y is very rare. Can I make groups and model count instead? Background/What I tried I want to know what the effect of the number of "...

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