Questions tagged [causality]

The relationship between cause and effect.

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113 views

using categorical variables in pre/post study

I have a continuous outcome variable, Y, that is a daily consumption score and want to study the impact of a policy change on a control group and 4 test groups t1, t2, t3 and t4. The policy change ...
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34 views

Unbiasedness of confounding variable models

This is a question based on work in this paper: https://dl4physicalsciences.github.io/files/nips_dlps_2017_14.pdf I am interested in causality and representations using probabilistic graphical ...
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421 views

How I interpretate a CCA plot (made with xlstat)?

Here are the 2 CCA (Canonical Correspondence Analysis) plot I'm trying to interpretate. I did them using the appropriate function in xlstat. I want to know how I should interpretate the fact that in ...
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24 views

Detection of unmodeled dependence

Given 2 joint groups Bernoulli trials: $X_i \sim p_i$ and $Y_i \sim q_i$, where $(X_i, Y_i)$ are binary outcomes of the $i$-th experiment, and $(p_i, q_i)$ are the probabilities of $X_i=1$ and $Y_i=1$ ...
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29 views

Causal inference from multivariate putative cause and univariate putative effect

Suppose we want to find out if observed multivariate binary random variable $\textbf{X}$ causes observed binary random variable $Y$ in presence of observed multivariate binary covariates $\textbf{Z}$. ...
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346 views

Seemingly impossible CIs for proportion mediated (package 'mediation')

I'm working with the "mediation" package for simulation-based causal mediation analysis. My question is: Why do percentile-bootstrapped CIs for the proportion mediated sometimes include impossible ...
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528 views

What distinct matching routines do exist?

In a seminar paper I'm discussing all possible matching routines. It turned out that there are quite many of them. Now I am looking for several answers: First, I discovered that some routines happen ...
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1k views

Causal Inference with Counterfactuals and A/B Tests

I am wondering if, instead of "paying for" an A/B test for all hypothesis' (designing an experiment, running it under controlled situation etc), a statistical analysis can be conducted on past data as ...
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1answer
3k views

Model 4 mediation PROCESS with dichotomous mediators

I'm doing a PROCESS Model 4 mediation analysis, where: X = Persuasion Knowledge (continuous) M1 = Brand Attitude (continuous) M2 = Brand Awareness, which consists of aided brand recall (dichotomous)...
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122 views

Choosing dimensionality reduction Technique

I am working with daily sales of products in a supermarket. The purpose is that of accurate forecasting. For each product sales I have many predictors, which include price,stockout,promotions of the ...
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1answer
101 views

Time series or causal modelling?

I have a dataset consisting of many product sales over time on a daily basis. I do know when promotions and discounts happen with four months in advance. When there are no promotions sales are 0 or ...
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22 views

Matching / imputing between experimental and control group on a specific (i.e. latent) variable

I am currently researching the impact of survey participation on subsequent behavior, i.e., does merely participating in an intention survey about fitness products influence post survey spending. As ...
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22 views

Situation where something autocorrelated is misidentified as being informative?

I work in finance, and there's a class of models that works something like this: Market A -> Market B Very simply, you theorise that market A predicts market B, and you build a model along the lines ...
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511 views

The difference between “within subject” experiment and “between subject” experiment

Consider the the situation you want to know whether a new medicine will help to reduce the blood pressure. Assume now you do a random draw from your target population, say you have 20 people in the ...
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2k views

Evaluating results of VAR (Vector Autoregression) using R

I am trying to evaluate the results of a prediction obtained with the R function VAR. I have reproduced an example with two time series so that others can also implement it (the data set is read from ...
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23 views

Multiple imputation with intermediate variables

Can intermediate variables be used in multiple imputation to predict missingness in covariates? Example: Suppose treatment X impacts Z which impacts Y. Now suppose you have control variables (C) ...
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27 views

After PHC hours were extended, we observed a reduction in ER visits for non-urgent care: how to determine causality?

I am from a Caribbean Island. Data was collected from the ER regarding visits for non-urgent care by residents of a rural area. In 2014, the total number of visits = 2,197. In 2015, the total number ...
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91 views

statistical test to compare numerical data pre and post intervention

For my research I will be comparing the mean number of screening tests performed before implementation of an intervention and after. The pre and post groups are not the exact same participants. The ...
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40 views

Find relationship in two time series datasets

I have two datasets: Ingested ingredients at a point in time e.g. | 24/04/2016 11:56:33 | Tomatoe | | 24/04/2016 11:56:33 | White rice | | 24/04/2016 14:34:01 | Mars Bar | Symptoms | 24/04/...
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308 views

Control group construction in Synthetic Control Method

I want to use the Synthetic Control Method to estimate the effect of the adaption of a new ballot institution (treatment) on fiscal policy. My sample consists of 20 units observed at 100 time points. ...
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90 views

Granger causality test vs my own custom causality test

I have a panel data regression with fixed effects, but for simplicity it is such that a lagged explanatory variable is significantly correlated with the dependent variable, which I believe is ...
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26 views

Coefficient of Quasi-Randomized Control Trial with different Treatment Intensity

I need some thoughts on the following problem which I have not been able to solve. I have thought of using different methods including OLS, FE, and PSM but I am not sure what to use. Here is the ...
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18 views

Can external cause ever be discounted?

We are often advised not to confuse correlation with causation. Fortunately techniques do exist to assess the likelihood that an outcome does indeed result from a cause. 1 2 But in some cases it is ...
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61 views

Methods of Treatment Effect Heterogeneity Estimation (Observation Data)

Given observational data, where a "treatment" is chosen by the unit of observation or not, are there any standard methods of ascertaining not just if the treatment has effect overall (ATT), but ...
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162 views

Binary logistic regression - SPSS

I did some regression analysis in SPSS using two binary variables: Biomarker X (0= low levels; 1= high levels), where 0 was the reference category and Obesity (0=no; 1=yes) ''Biomarker X'' was taken ...
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1answer
106 views

Challenging Propensity Score/Causal Inference Problem

I am reaching out to the Cross-Validated statistical community seeking suggestions on a challenging problem on which I'm working. I've been asked to look into a problem related to electronic ...
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23 views

Isolating influence of sampling from actual change

Say I want to evaluate teams' batting coaches in a hypothetical baseball league. It's an unusual league in that there is no control over (and large fluctuation within) the number of at-bats each ...
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56 views

Need a statistic for comparing “strength” of Markov blankets in a Bayesian network

Working with Bayesian networks. I take a given network structure and fit its parameters on data. I am looking for a statistic based on those parameter estimates that allows me to compare Markov ...
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219 views

Mahalanobis Distance Matching

When doing Mahalanobis matching to improve covariate balance for causual inference, how come if the treated units aren't subsampled only the control covariance matrix is used $S_c$ as opposed to the ...
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77 views

$3^3$ factorial design

Suppose in a $3^3$ factorial design, factor A has three levels. We want to test the significance of A and after setting hypothesis $$H_0:\alpha_i=0 \quad\text{for}\quad i=1,2,3 \quad\text{Vs.}\quad ...
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2k views

Is there evidence of mediation? Need help with interpretation of mediation analysis results

I have performed a mediation analysis. I have an independent variable T, a mediator M, and outcome Y. (All 3 variables are binary, and I use logit.) (While I used Stata ...
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29 views

Adjusting for a mediator to capture cross sectional relationship

We are fitting a linear model using cross-sectional data to inspect the relationship between some exposure and an outcome (disease status, measured continuously). Duration of disease was also captured ...
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61 views

Meta-analysis: Talking about power and inference (to power)

I need a little help or reassurance concerning how to explain power "to power", i.e. to decision makers that are not well versed in statistics. The problem is this: I have done three empirical ...
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74 views

Identifying what contributes to the increase in one variable

Say I have a dataset with several continuous and categorical variables, and I want to identify what variables (values or properties of these variables) may cause one of the continuous variables to ...
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119 views

Do you need causal models when doing counterfactual predictions?

I am modeling the impact the number of a certain type of company (bottom of pyramid (BOP) companies, ie. companies that cater to the poorest consumers) have on market price. I considered the ...
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1answer
61 views

Inference from a sometimes-random time-series

Let's say we have two cointegrated time-series, $Y_{1}$ and $Y_{2}$, and I want to assess the causal impact of $Y_{1}$ on $Y_{2}$. There is good reason to think that both variables are influenced by a ...
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201 views

Examples for teaching: Sometimes we CAN infer causality.

There have been threads here before which posted links of the media attributing causality to correlational studies, and links to those studies have been posted. It seems as if we are always focusing ...
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65 views

Estimating the probability of causation based on finding a correlation, including experimental details

Say there is a hypothesis that A causes B (A -> B), and some likelihood that the hypothesis is correct (AB1%). Now, an experiment is run that claims to find a correlation between A and B. What I ...
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145 views

Regression discontinuity and regression to the mean

Regression discontinuity designs aren't susceptible to regression to the mean. I'm not quite sure why, though. The best I can come up with is that regression to the mean is a phenomenon that occurs ...
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131 views

Power of simple linear regression when the independent variable is correlated with the true causal variable

Consider the simple linear regression model: \begin{align*} y = \beta_0 + \beta_1 x + \epsilon \end{align*} Let $b_1$ be the least squares estimate of $\beta_1$, assuming the variance of error $...
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131 views

Interrupted time series control group

I'm conducting the analysis on readmission rate for a hospital unit between 2009 and 2012. I have a list of "historical" data where patients did not have the intervention. I then have a different set ...
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4k views

Econometrics: Sargan test

Here are 3 questions about econometrics and R codes. Test the endogeneity of the variable EDUC: ...
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288 views

Counterfactuals for Variables with Negative Values

Lets imagine I have estimated the following simple linear regression model: $y_{i} = 10 + 0.5x_{i} + \varepsilon_{i} $, and want to work out the counter-factual, or what would $ y_{i}$ be in the ...
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2k views

An alternative to “Granger Causality” test when (short) time series are not stationary?

I have two short time series (x and y), and I wish to find out if x "effects" (is correlated with) y. Obviously, since the two are time series, using a simple correlation is the wrong way to go. I ...
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20 views

Difference-in-differences model with a matched control group

I need to run a difference-in-differences (DiD) model, but I'm not sure how to construct a formula for this. The problem is that the timing of events affecting the treatment group is not uniform, like ...
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1answer
54 views

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 $k$ ...
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1answer
38 views

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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24 views

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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1answer
21 views

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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21 views

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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