# Tagged Questions

Causal inference tries to quantify the effect of a change in $X$ on $Y$ whilst holding constant or eliminating all other relevant factors which might influence this relationship.

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### Multilevel model for causal inference using observational data

I am trying to follow the lecture notes by Imbens/Wooldridge (http://www.nber.org/WNE/lect_10_diffindiffs.pdf) on difference-in-differences estimation. In page 4, they discuss the general framework ...
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### group fixed-effects, not individual-fixed effects using plm in R

I am analyzing some data to evaluate the impact (causal effect) of a program that is delivered at group level (a village). The outcome of interest is measured at the individual level (individuals ...
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### Transfer function in forecasting models - interpretation

I am occupied with ARIMA modelling augmented with exogenous variables for promotional modelling purposes and i have hard time explaining it to business users. In some cases software packages end up ...
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### Explaining why the slope varies in varying slope model?

When I fit a multilevel varying slope model, it is easy to summarize the variation in slope. However, I have not yet seen any materials that discusses how to explain such variation (i.e. what about ...
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### 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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### Is there any correlation or causation here?

I have the following data, where 2 properties (P1 and P2) can be either True or False ...
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### How to find three probabilities with two different values or ratings?

I would like to know how to find three probabilities of two values.... Specifically...I want to know the three soccer venues (HOME DRAW AWAY) proabilities with two ratings... Example: I have two ...
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### From Identification to Estimation

I'm currently reading Pearl's piece (Pearl, 2009, 2nd edition) on causality and struggle to establish the link between nonparametric identification of a model and actual estimation. Unfortunately, ...
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### Would a simple OLS regression work with this example?

First and foremost I would greatly appreciate any help you can provide me with. I am writing my undergraduate thesis on the rise of populism in France. The relationship I am trying to better ...
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### Does adjusting for superfluous variables bias OLS estimates?

The usual textbook treatment of adjusting for superfluous variables in OLS states that the estimator is still unbiased, but may have larger variance (see, for example, Greene, Econometric Analysis, ...
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### How to program automated shrinkage for a subset of terms in R?

I've got data from a randomized experiment that includes a lot of covariates. I'm interested $\delta$ from a model of the form $y = g(\delta T + X'\beta+ \epsilon)$, where $T$ is randomly assigned and ...
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### Confusion about features selection for inference analysis with lm/glm

I need a bit of tutoring about grasping the true meaning of linear regression analysis. I'd like some help in understanding well the relationships between predictors and and the meaning of adding and ...
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### Propensity Score Analysis with continuous treatment

I have an observational dataset of about two dozen observed variables (continuous or discrete), plus a continuous variable of which I would like to measure the causal impact of on my dependent ...
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### 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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### 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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### Detecting parameter influence

I have a data set consisting of a system's responses to various test configurations. Every test configuration corresponds to a different parameter set. These parameters can have either continuous ...
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### Identifying What Causes a Variable to Increase

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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### How can we combine learnings from multiple experiments in a single causal model?

I would like to use a causal network modelling to model the interaction of several variables and the effects of interventions. I have measurements for all priors of the model, that is without any ...
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### 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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### Is this mediation or a simple path?

This is my model adapted from a study. I want to know whether I can only study it as a path analysis without studying mediation effect (1 $\longrightarrow$ 5 direct effect, as well as indirect ...
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### 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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### Dropped cases from matched studies

We have cohort data and a rare exposure which we are matching to controls in a large epidemiologic dataset. The matching variable is a deidentified neighborhood indicator (cluster) which guarantees ...
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### Real examples of Correlation confused with Causation

I'm looking for specific, real cases in which a causal relationship was inappropriately inferred from evidence of a correlation. Specifically, I'm interested in examples that meet the following ...
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### Endogeneity & IV = model misspecification?

I'd like to raise a controversial point: if you need instrumental variables, your model is wrong. Basic endogeneity problem and the IV solution Let us suppose the basic framework of endogeneity and ...
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### Difference between Research Design and Experimental Design

What is the difference between Research Design and Experimental Design? I can't see any difference. Both of them need to establish Causality. Both of them are the arrangement for collection and ...
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### Computing inverse probability weights — conditional (multivariate) density estimation?

The general version: I need to estimate $f(A | X)$ where $A$ and $X$ are continuous and multivariate. I'd rather do it nonparametrically because I don't have a good functional form in mind and ...
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### Google trends data for interest

I was discussing about the popularity of some terms and used google trends to conclude in the decrease of their popularity. Here is an exemple of the queries for some of the biggest french ...
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### Average of percentages / prove causal relationship between sale dates & margin sales

I just wanted to make sure I'm right here. I have a situation where I need to prove that on days where we sell more than 10 items, our margin (sale price vs. suggested price) goes up. I'm not really ...
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### Graphical and Statistical Tests for Robustness of Sharp RD

I'm doing sharp regression discontinuity design with my treatment variable $$D_i = \begin{cases} 1 \enspace \quad \text{if x_i \geq \overline{x}} \\ 0 \quad \text{otherwise} \end{cases}$$ where ...
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### Proving that the variance observed in time series A is due to the variance observed in time series B

I'm testing the hypothesis that the the variance observed in the number of medical consultations felt from 2009 through 2013 is due to the variance in user fees price, and not due to something else. ...
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### Measurment error for two variables

I am interested in estimating the effect of security S on crime C in a given city over time (eight quarters) for twenty cities, so it's panel data. The problem is, instead of actual security spending ...
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### Ranking of causal models

I remember seeing a paper that ranked causal statistical models, published by some research body, by quality in terms of generalizability or some similar facet(s). This would be a "hierarchy of ...
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### Causality in microeconometrics versus granger causality in time-series econometrics

I understand the causality as used in microeconomics (in particular IV or regression discontinuity design) and also the Granger causality as used in time-series econometrics. How do I relate one with ...
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### “Explaining” a time series - conceptual explanation needed

Imagine I have a time series for an animal population and a time series for a climatic variable during the same time period and at the same location. Unfortunately the data are observational (i.e., no ...
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### Correlation and regression [duplicate]

Can there be negative correlation but the regression line has a positive change when there is an increase in the independent variable?
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### How do instrumental variables address selection bias?

I'm wondering how an instrumental variable addresses selection bias in regression. Here's the example I'm chewing on: In Mostly Harmless Econometrics, the authors discuss an IV regression relating ...
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### 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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### Infer causality with high collinearity

I recently started to ask myself how to measure the impact of education on indexes like GDP: what is the outcome of mathematics or computer science on GDP, at the country level for instance. In this ...
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### Under what circumstances is regression discontinuity preferred to differences in differences?

I am looking at the adoption of universal health care coverage for children age 6 and under in a country. The take-up rate was practically 100%. I want to know the impact of having coverage on ...
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### 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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### Difference-in-Differences Estimator for Logistic Regressions

I have a pre-post intervention study with four groups: 1) Pre-Intervention Control, 2) Pre-Intervention Treatment, 3) Post-Intervention Control, and 4) Post-Intervention Treatment. The outcome is a ...
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### Estimating a confidence interval around the average of an interacted treatment effect

I've got a causal inference situation with heterogeneous treatment effects. In addition to simply estimating coefficients, I'd like to get an average effect of the treatment at the covariate values ...
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### causal inference with correlated multivariate outcomes

I've been struggling with how to think about the causal estimate of a program on two outcomes, when one of the two outcomes affects the other outcome. It seems sort of like simultaneous equations, ...
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### Guessing test question answers from scores

My teacher likes to give online quizzes that are about 20-30 questions long. Every student has the same questions in the same order. We are not told after taking the quiz which questions we got wrong, ...
I'm not sure why in Mostly Harmless Econometrics, last paragraph of p. 55, the expectations of $f_{i}(s-4)$ is taken and the expectation of $f_{i}(s-1)$ is not. The text reads: Conditional on ...