# 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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### Choice of referent twin in twin difference model

Carlin (2005) points out that mixed effects models specifically for twin data can be simplified by calculating differences between paired clusters. This allows for modeling specifically the within ...
115 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 ...
1k views

### Relation between causal inference and prediction (classification and regression)

I was wondering what relation and differences are between causal inference and prediction (classification and regression)? For example, In prediction, we have predictor/input variables and ...
98 views

### Relative efficiency of matching versus adjustment to handle confounding effects in highly disproportionate populations

I am reviewing a paper where the authors compare cancer outcomes (binary) between two groups, one having a small sample size of 200 and the other having over 55,000. The authors then claim that, due ...
288 views

### Causality, omitted variable bias

This might be a basic question, but I want to be sure that what I'm doing is right. I have a model that suggests that variable X causes both Y and Z. When I regress Y on X, or Z on X, I get positive ...
113 views

### I have GBs of Event-Based Data. How do I figure out causation?

I have a lot of event-based data about users of our website. For example, data in the format (verb, timestamp). There's about 10 or so different verbs (call them A, B, C, etc). I'm interested in ...
1k views

### Do we need Overlap/Common Support in case of a parametric regression?

If I want to make a causal statement based on selection on observables. One typically assumes "Common Support" (/"Overlap") - which means that for any value of the confounding variables X a unit i can ...
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### 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 ...
655 views

### Big Data vs multiple hypothesis testing?

Nate Silver in his excellent "The Noise and the Signal" warned that we are much in awe of Big Data. But, that Big Data predictions in many fields have been disastrous (financial markets and economics ...
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### Causality test for logistic regression

For time series there is the Granger causality test. Is there some causality test for the logistic regression?
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### Formula for one-sided Hodrick-Prescott filter

I am not very familiar with filters. The Hodrick-Prescott filter as one can find it e.g. in wikipedia is two-sided. I also found an R implementation for this in the R package mFilter. There the filter ...
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### Why arrange variables by causality in bivariate regression?

Suppose we have variables $(X,Y)$ and we have theory tell us that $X$ $\overset{\text{cause}}{\implies} Y$. Perhaps they're time-series variables and it would be common to see something like this: ...
762 views

### What if only control variables are significant in a differences-in-differences analysis?

Regarding the standard DID model: $$y=\alpha+\beta_1\text{treat}+\beta_2\text{post}+\beta_3\text{treat⋅post}+u$$ What exactly does it mean if say $\beta_3$ is not statistically significant, but ...
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### Introduction to causal analysis

What are good books that introduce causal analysis? I'm thinking of an introduction that both explains the principles of causal analysis and shows how different statistical methods could be used to ...
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### Causal stats with one event and multiple time series?

I've worked with certain causal/predictive techniques when handling two time series, but this problem is different from what I am used to and I'm not sure how to proceed. I would like to see the ...
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### What test should I use to determine if a policy change had a statistically significant impact on website registrations?

A client's website was operating under a certain policy for membership sign ups for over a year. At the start of October 2012 the client implemented a new policy for sign ups that was supposed to ...
909 views

### Fuzzy regression discontinuity design and exclusion restriction

In a fuzzy regression discontinuity design, what does the exclusion restriction look like in terms of a conditional expectation between the instrument in the first stage and the error term in the ...
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### How to account for a regressand affecting a regressor?

I forget the terminology, but this happens when you regress, say, $Y$ on a list of variables, and you suspect that $Y$ affects, say, $x_3$ in addition to $x_3$ affecting $Y.$ I forget how this is ...
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### Causation implication

I recently read an article about how you can increase longevity by sleeping less. This article, like many others I've read, references a statistical study and implies that causation was found between ...
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### Proving Causality with t-test/regression

Earlier today I was discussing statistical analysis software with a colleague of mine. My colleague had primarily used SPSS in previous work for performing t-tests, anovas, manovas, and other ...
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### Effect of one independent variable of several dependent variables – best strategy?

I have a question regarding which analysis strategy is best suited for our objective. In an exploratory study based on data from a survey we conducted ourselves in India, we are analyzing the ...
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### Heckman selection model with difference-in-differences specification

Following my question on Tobit with DiD specification I am wondering if it is possible to estimate a heckman sample selection model with a Difference in Differences specification? For example in ...
2k views

### Is it possible to have a variable that acts as both an effect modifier and a confounder?

Is it possible to have a variable that acts as both an effect (measurement) modifier and a confounder for a given pair of risk-outcome associations? I'm still a little unsure of the distinction. I've ...
968 views

### Random assignment: why bother?

Random assignment is valuable because it ensures independence of treatment from potential outcomes. That is how it leads to unbiased estimates of the average treatment effect. But other assignment ...
689 views

### How to avoid the problem of two-way causality?

I am studying the effect of social capital on households' income. I am doing multiple regression to estimate this effect. For this, I have households' income as dependent variable and social capital ...
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### Formal definition of random assignment

I am looking for a formal definition of random assignment. Let $\mathbf{Z}$ be a vector of treatment assignments in which each element is 0 (unit not assigned to treatment) or 1 (unit assigned to ...
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### Implication / Interpretation of long term equilibrium VECM

I want to test the influence of exchange rates on a price index and struggle with the interpretations. My variables are I(1) First, I ran an OLS on first differenced variables which indicated a ...
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### Difference in Differences: id switches between treatment and control group

In my difference in differences model firms $> x$ belong to the treatment group whereas firms$< x$ act as control. I have a two period model: In $t_1$ firm $i$ is $> x$ and thus ...
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### How do I estimate a differences in differences model when the dependent variable has many zeros?

Is there any way to run an OLS difference in differences model when the dependent variable (investment) has lots of observations which are truly zero? I don´t know how to add clarifications. My ...
440 views

### Clustered standard errors in 2-period Dif-in-Dif?

in order to rectify invalid t-stats because of autocorrelation in Difference-in-Differences (DnD) models, Duflo et al (2004) propose (among other solutions) to collapse data so as to have a ...
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### Why use control variables in differences-in-differences?

I have a question on the differences-in-differences approach with the following standard equation: $$y= a + b_1\text{treat}+ b_2\text{post} + b_3\text{treat}\cdot\text{post} + u$$ where treat is a ...
15k views

### X and Y are not correlated, but X is significant predictor of Y in multiple regression. What does it mean?

X and Y are not correlated (-.01); however, when I place X in a multiple regression predicting Y, alongside three (A, B, C) other (related) variables, X and two other variables (A, B) are significant ...
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### Must there be “an effect to be mediated” in mediational analysis (i.e., must IVs & DVs be correlated)?

Baron and Kenny outlined several steps to aid in determining if a mediational analysis is appropriate to test a particular hypothesis. The very first step was "Show that the initial [independent] ...
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### How to control for industry effects in regression?

Right now I'm working on an analysis of influence of cultural aspects on investment mode preference. However I have to control for many other factors, for example industry, since some industries, for ...
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### Inductive vs deductive Inference

I am curious to know exactly, what are the (possible) differences between inductive and deductive statistical inferences in applied statistics. Suggestions for some good resources to learn their ...
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### Differentiating correlation and causation using conditional probablity

I'm trying to understand the difference between causation and correlation using conditional probabilities. From what I understand, one may quantify causation by $P(E_1|E_2) / P(E_1)$. For example, ...
4k views

### How do you find causal relationships in data?

Lets say I have a table with columns "A", "B" Is there a statistical method to determine if "A" causes "B" to happen? One can't really use Pearson's r, because: it only tests the correlation ...
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### What to conclude when you fail to find an association in an epidemiological study?

Normally when somebody finds an association in an epidemiological study people are quick to point out that it doesn't prove causality, that there are problems of missing co-founders, that it is at ...
1k views

### Identifying the time lag between cause and effect

What approaches exist to observe the time lag between two variables? I need to analyze the relationship between blood pressure and some other factor, such as exercise. The data set I am drawing from ...
1k views

### Criticism of Pearl's theory of causality

In the year 2000, Judea Pearl published Causality. What controversies surround this work? What are its major criticisms?
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### Does causation imply correlation?

Correlation does not imply causation, as there could be many explanations for the correlation. But does causation imply correlation? Intuitively, I would think that the presence of causation means ...
11k views

### Interpreting Granger causality test's results

I'm trying to educate myself on Granger Causality. I've read the posts on this site and several good articles online. I also came across a very helpful tool, the Bivariate Granger Causality - Free ...
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### Matched Analysis with Complex Survey Data

Complex survey data is that typically found produced by the National Center for Health Statistics (NCHS) or the NSLY; it typically contains information on PSU, strata, and weights. To make nationally ...
942 views

### How much sub-questions impact one ordinal question in a survey

I have a variable NPS which is an item on a survey, the answer format is ordinal, 0 to 10. Then there are sub-questions on the same survey, some are ordinal, some are categorical. I would like to ...
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### Does control get us closer to or farther from causation?

In logistic regression with an N of 40,000, purchase decision is unrelated to price. However, with certain demographic variables controlled, price can show a positive coefficient of meaningful ...
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### Is this a valid approach to testing a hypothesis about the relationship between two variables?

I am trying to test a hypothesis I have about consolidation in the real-world market for a certain machine. (My apologies in advance for obfuscating a bit here, but some of the data is proprietary and ...
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### How wise is the use of ANCOVA when groups differ on the covariate?

In this case I presume loss of ANCOVA power, so I don´t know what type of analysis should I run next. There was significant difference in covariate between groups (p=0,008). Is there some solution? ...
2k views

### Inverse probability of treatment weighted (IPTW) estimator for a binary outcome

Recently, there are several estimators have been proposed to estimate the average treatment effect (ATE) in observation studies, such as IPTW, doubly-robust estimator, etc. It fully makes senses to me ...