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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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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296 views

What test is this for endogenous variables?

Can somebody tell me whether the following R code (for econometrics endogenous variables) is for a Hausman test, a Nakamura test, or some other test? ...
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43 views

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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738 views

How can I represent Conditional Probability Table based Bayesian Networks in Winbugs? [closed]

Winbugs seem to support either stochastic or deterministic relationship between variables. However, many Bayesian Networks represent relationships between variables using conditional probability ...
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143 views

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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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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What is the difference between effectiveness and efficacy in determining the benefit of therapy 'A' on condition 'B'?

The context of this question is within a health framework i.e. looking at one or more therapies in the treatment of a condition. It appears that even well respected researchers confuse the terms ...
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Interpretation of positive and negative beta weights in regression equation

I received this elementary question by email: In a regression equation am I correct in thinking that if the beta value is positive the dependent variable has increased in response to greater ...
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23 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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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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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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26 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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Choice of dependent variable: Differencing or Controlling?

I was running some analysis where I suspect that a treatment $D$, has opposite effects on two variables $Y^A$ and $Y^B$. To show that, I was thinking about two strategies: 1. Differencing Running ...
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263 views

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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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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2answers
465 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 ...
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85 views

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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1k views

Statistics and causal inference?

In his 1984 paper "Statistics and Causal Inference", Paul Holland raised one of the most fundamental questions in statistics: What can a statistical model say about causation? This led to his ...
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2k 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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120 views

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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41 views

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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586 views

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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1answer
6k 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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2k views

Are mediation analyses inherently causal?

I am interested in testing a simple mediation model with one IV, one DV, and one mediator. The indirect effect is significant as tested by the Preacher and Hayes SPSS macro, which suggests the ...
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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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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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1answer
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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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40 views

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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Does randomization really allow us to make claims of causality?

Lets say two groups are compared. Subjects are randomly assigned to each group, then a treatment is given to half while a placebo is given to the other half. All aspects of the experiment (order of ...
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151 views

Do edges in directed acyclic graph represent causality?

I am studying Probabilistic Graphical Models, a book for self-study. Do edges in a directed acyclic graph (DAG) represent causal relations? What if I want to construct a Bayesian network, but I am ...
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305 views

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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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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5k views

What do “endogeneity” and “exogeneity” mean substantively?

I understand that the basic definition of endogeneity is that $$ X'\epsilon=0 $$ is not satisfied, but what does this mean in a real world sense? I read the Wikipedia article, with the supply and ...
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46 views

“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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51 views

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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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 ...
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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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1answer
62 views

Interpretation of lasso recovery results

When people say that lasso regression can under certain assumptions recover "the support", i.e. non-zero regression weights, what does this mean? This cannot mean causal recovery, because Pearl has ...
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2answers
609 views

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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29 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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Roy model question

I am referring to G.S. Maddala: Limited Dependent and Qualitative Variables in Econometrics, pages 257-258. I add the relevant screenshots here: My question is, why is ...
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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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6answers
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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 ...
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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, ...
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30 views

Causal Analysis

I want to do "Nutritional Causal Analysis". Basically my objective is to identify possible factors associated with acute malnutrition in children under five years of age in developing countries. What ...
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1answer
131 views

Graphical models for correlation of random variables and prediction of hidden observations

I am studying about Graphical Models and I came up with a simple example but I am not sure which kind of technique (HMM, DGM, MRF) would be able to help me with that. Imagine we have three balls that ...
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1answer
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Average causal effect of one year increase in schooling vs a four-year increase in schooling

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 ...