Questions tagged [causality]

The relationship between cause and effect.

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35 views

Does any test actually prove causation? [duplicate]

I was once critiqued for using a "wrong" test because the test I chose didn't actually prove causation. I admit that I'm not a statistician. My education is very incomplete. What statistical ...
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35 views

Can Granger causality be used in average values?

I have gene expression data for several genes in different time points (but I guess the type of data doesn't make any difference for this question). I would like to use Granger causality to see if ...
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42 views

Causal Inference of Between-Group Differences in Time Series Data

I'm relatively new to time series data/causal inference (am working my way through Mostly Harmless Econometrics as we speak). Though, I'm still not sure how to appropriately test between-group ...
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14 views

percentage boost in a correlated value

In a psychology article I read that: “modesty predicted increased emotional intelligence (. = .43, CI [.35, .51]), which predicted self-esteem (. = .55, CI [.46, .63]), and in turn predicted greater ...
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46 views

Missing at Random (MAR) vs. Unconfoundedness (conditional exchangeability)

I thought unconfoundedness is just a special case of MAR under the causal inference framework. By unconfoundedness $P(A=a|X,Y^{a=0},Y^{a=1})=P(A=a|X)$. By MAR, $P(A=a|X,Y^{a=0},Y^{a=1})=P(A=a|X,Y^{a}...
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Accounting for imbalance in number of time points per observation to estimate average treatment effect

This is a follow up to this question. How can someone estimate the Average treatment effect (ATE) when not every observation has the same number of treatments/exposures? This is not dropout because ...
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28 views

How do I know which of the two time series is lagging and which is leading?

I have two time series that are highly correlated, but occasionally one moves out of line with the other. Someones the other will follow and catch up with the first. Sometimes the first will revert ...
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21 views

Using propensity scores to calculate average treatment effects

I have obtained class probabilities for 0 or 1 classes ("control", "treatment"). can I also assume that these are also the propensity scores. If so, how do i use these probabilities or propensity ...
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1answer
503 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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62 views

need help understanding propensity score matching (what is my treatment vs my outcome)

suppose I want to incorporate propensity score matching in analyzing sales. Last year, I sold 100 of 300, so my ratio is 33.33%. This year my items costs 5% less and I sold 300/600, so my ratio is ...
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230 views

What does it mean for “A is confounded with B” [duplicate]

Can you give me an example for one variable being confounded with another? (I've read the tag wiki for "confounding" but I'm still confused.)
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218 views

Finding causal relationship between two sets of time series data

I want to see if a change in the volume of Google searches of a company affects that company's stock price. I have time series data from Google Trends and daily close price of the stocks in question, ...
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39 views

Cane someone please give examples of correlations that indicate, with other mechanisms, causation?

My title basically says it all. Can somebody please give some good, interesting examples of correlations with causation? The causation need not be confirmed. It just need to be debatable, plausible ...
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97 views

logic behind additive Noise Models?

I am new to statistics, reading the elements of causal inference: On section 4.2.1 Additive Noise Models, appears: Left regress Y on X. Right regress X on Y The fitted functions are shown in the ...
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60 views

Adjusting for non-confounders based on DAG

I've drawn the following DAG to represent my data generating process I'm interested in estimating the effects of G1 and G3 on <...
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37 views

Should I drop variable highly correlated with independent variable? (Causal inference)

I estimate OLS: Y = c + b1*x1 + ....+ bn*xn +err corr (Y, x1) = 0.8, Corr(x1,err)>0 Should I drop variable x1? What kind of biases would I have in both cases: with and without x1.
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109 views

Non-stochastic vs Stochastic regressors and sampling distributions and causation?

I was wondering if I understand these correctly. Would an example of a stochastic regressor be weather? so when thinking about the sampling distribtuion and causality, I would think of repeated ...
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1answer
100 views

Causality between two binary time series

I have the following sample of a big dataframe: ...
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21 views

Drawing a causal conclusion about a change in production code

We had a change in our production code which we did not perform A/B test for. A few days after the product is changed, we have been seeing a significant drop in our quality metrics. Is there any way ...
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1answer
40 views

Causal Inference in Mortality Rates

I was wondering how does one study the average treatment affect in scenarios suchs as mortality rates. For example: suppose we want to study the effect that a certain medicine has on the mortality ...
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Two-step residualization in fuzzy RD

I'm adopting a two-step residualization approach in fuzzy RD, should my first stage also include a polynomial of running variable (age)?
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1answer
33 views

How to generate a model for the causal effects for a Panel dataset

I have a dataset such as hourly sales data:(0:00~23:00) by products, after 18:00, the platform will give a discount to several products to speed up the sales. If I want to know the causal effects of ...
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103 views

The impact of other continuous variable on the DID estimate

I have searched around but didn't have any luck. I am trying to estimate and then compare the DID estimates of the effect of a Treatment on Life-expectation across different Income levels, to know if ...
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58 views

Exploring Causal Relationship in R

I need to explore if there are any causal relationships in my dataset, but the data has 30 points per year (for 30 different countries) and only 10 years worth of data. Accordingly, I can't use ...
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45 views

Are feature importances from tree based models directly actionable for business?

If my response variable say is "has_repurchased" [0 or 1] and I have all customer level features. Can I rank the features in order of importance from the random forest model and report them as whats ...
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103 views

IPW for the effect of treatment on treated with a continuous treatment

I've been banging my head against the wall trying to figure out how to construct inverse probability of treatment weights (IPTW) for the population average effect of treatment on treated (PATT) with a ...
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2answers
222 views

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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40 views

Causality logic appears reversed. What's the explanation?

In reading Detecting Causality in Complex Ecosystems I came across the following passage: Our alternative approach [...] tests for causation by measuring the extent to which the historical record ...
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104 views

Is this causal effect identifiable? It includes a mixture of observational and interventional data with selection effects

The DAG of the model is below. We wish to estimate P(attitude | do(exposed)). moving up from the bottom of the dag: we ...
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81 views

Causal model: Controlling for moderating effect of confounder (rather than the confounder itself)

My linear regression model can be described by the following causal graph: I want to explain the sign of the causal effect of $X$ on $Y$, but unfortunately cannot measure $Z$ directly. Thus, I can ...
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38 views

do not need many controls with big data?

I am looking at a paper which uses a large panel data, 1 million observations, a dozen variables. I recall that in a discussion another one has the following comments: In structural models like ...
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62 views

Deterministic Assignment to Treatment

When estimating causal effects, you want to compare individuals as similar as possible. It is from this need that stems the exchangeability (/ignorability) or conditional exchangeability (/ ...
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63 views

Problem in creating causal model for delay analysis

knock-on" are defined as delays caused by previous late departures or arrivals. I am trying to create a model which can help predict the arrival delay of the next flights. But I don't know where to ...
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1answer
120 views

Pre.intervention and post.intervention should be contiguous in CausalImpact?

I am running a CausalImpact analysis on a time series and my pre.period goes from 01.01.15 to 30.03.15. I want my post period to be from 15.04.15 to 17.04.15. Is it ok if I create a time series that ...
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425 views

How to establish and prove causality between two variables? [duplicate]

I want to establish causality between two variables/attributes of some time series data. Is there any method to prove and establish the causality mathematically?
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65 views

Potential bias in a study design

I am trying to design a study regarding Diabetes. I have patients with test results of some indicator about their situation - sugar levels, but not in the classic sense that you may know. Every ...
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246 views

In Inverse Propensity Score Weighting, is it possible to find an explicit solution to the estimator by way of Jacobians?

In IPSW, a propensity score model is specified (usually an inverse logit) on a set of covariates, then from that, we use Weighted Least Squares regression to obtain the estimates. However, I am ...
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16 views

Matching with partially-observed covariates?

Context I have a randomized controlled trial where units $i \in N$ have one of two possible values (A or B) on variable x such that $x_i \in \{A,B\}$. Assume equal numbers of observations for all ...
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75 views

How to sample $N$ Bernoulli random variables given a fixed number of successes ahead of time without collisions?

Suppose that I have $N$ units and that each unit has a probability of being treated, $p_i$ for $i = 1, \ldots, N$. Treatment is indicated as $1$ and non-treatment is $0$. Suppose that $p_i$ turns out ...
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48 views

Sharp Regression Discontinuity (RD) for one part of the sample, RCT for another?

I have a study where schools' 4th graders are randomized into treated and controls (at the school level, i.e. there are treatment and control schools). Within each treated school, treatment follows a ...
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59 views

How can a valid conclusion be drawn despite the presence of many unknown confounding variables?

Specifically, I am trying to understand the above question in the following context: 'John thought that there was a difference in breathing when lying down compared with when sitting on a chair. He ...
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132 views

How to estimate Complier Average Causal Effect?

In an experiment, in addition to the assignment for every experimental unit, you also know the identity of some of the compliers, but not all. How to use this information to estimate the causal ...
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2k views

Identification assumptions and causal relationships

I'm new to econometrics and I'm having a hard time answering if the following statement is true or false: "In regression studies, making adequate identification assumptions is sufficient for ...
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279 views

Reverse causality between predictors, interactions and results' interpretation

In my model I have clear reverse causality between two predictors. I am mainly interested in esitmating the interaction between the two predictors mentioned above. I am wondering how this form of ...
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190 views

How can I infer causal relationships in this case?

I have a philosophical question about causal relationships inference. Suppose we have UCBAdmission data, where different gender and different department have different admission rates. ...
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1answer
564 views

Causality of the regression [duplicate]

I have the same results for two regression 1) y= number of board directors in t+1 x= a dummy variable with 1 if there is at least an institutional investor among the shareholders in t. 2) y= a ...
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429 views

Causal Impact and using multiple control series with their regressors

Hi all I am analyzing several DMA's for campaign effectiveness using the CausalImpact package by Kay Brodersen. I have data for participants and non-participants INCLUDING their contemporaneous ...
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186 views

Adjusting for confounders when the investigated exposures are gene mutations

I'm delving into causality and directed acyclic graph for choosing the right covariate structure for multivariable regression analysis. Reading Pearl work, I understood that one should adjust only ...
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228 views

How to distinguish a causal chain model from a double effect model?

I am used a linear mixed model on two datasets (two different species), with the same explanatory variable (an environmental variable) for fixed effects. I then select the top 0.1% response ...
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1answer
131 views

Analyzing the impact of change in a time series on another

I have two time series data: $x_t $ and $y_t$. I have developed an algorithm to detect unusual changes (activities) on my $x_t$ series, so that whenever there is a change detected (based on some ...