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.

learn more… | top users | synonyms

2
votes
1answer
141 views

Is it okay to run CausalImpact in R on successive portions of a time series?

We’re doing some advertising tests with test and control groups very similar to the example in the Google Research Causal Impact publication except we’re doing state tests and not DMA. I just have a ...
2
votes
2answers
60 views

Causal inference from Cross sectional study

As far I know that, causal inference can make for longitudinal study. Is their anyway way to make causal inference from cross sectional study design? If yes, how can I do this? Please share if any ...
2
votes
0answers
10 views

How can I compute cross-correlation and auto-correlation in R using pooled data?

I'm trying to perform a lagged linear regression on time series data sourced from ~10,000 hospital patients, for the purpose of estimating causal relationships between administration of a drug and a ...
0
votes
0answers
15 views

Dealing with constraints in probabilistic graphical models

Suppose I have a graphical model with i.i.d. $\Lambda_i \sim exp(\lambda),\ \ i = 1,...,n$, and $\bf{\Lambda} = \sum_{i=1}^{n}\Lambda_i$. Imagine that that these $n$ lambda and this capital ...
0
votes
0answers
19 views

How to identify the underlying mechnism in regression (to preserve the causality)?

everyone,I recently encounter a problem when doing some empirical work. Say, with a cross section dataset,I'm studying the effect from A to Y, including a branch of control variables X,of which A is a ...
1
vote
1answer
28 views

How to do regression if one is not sure of dependent variable?

I have data on age, gender, height and weight of subjects, and also levels of 2 chemicals in blood of these subjects (chem1 and chem2). It is not clear whether chem1 affects chem2 or chem2 affects ...
1
vote
0answers
11 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 ...
9
votes
2answers
189 views

Why is using cross-sectional data to infer / predict longitudinal changes a Bad Thing?

I'm looking for a paper which I hope exists, but don't know if it does. It could be a set of case studies, and / or an argument from probability theory, about why using cross-sectional data to infer / ...
11
votes
1answer
152 views

What are the main differences between Granger's and Pearl's causality frameworks?

Recently, I ran across several papers and online resources that mention Granger causality. Brief browsing through the corresponding Wikipedia article left me with the impression that this term refers ...
0
votes
1answer
38 views

Should I use the t-test or the Wilcoxon rank sum test given these qqplots and Shapiro-Wilk stats [duplicate]

I have 4 groups and I want to test if the pairwise difference in means are significantly different. There are 6 pairwise differences. The QQnorm plots of the 4 groups look like this: The ...
1
vote
1answer
460 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? ...
2
votes
2answers
30 views

Names for some canonical directed causal graphs/illustrations of some canonical causal relationships?

Certain names are used for structures or node relationships that appear in acyclic, directed graphs (DAGs). Often these DAGs are interpreted causally. Here's a partial list for relationships that ...
1
vote
1answer
22 views

Establishing causality under conditions of certainty

I'm currently reading "Causality: Models, Reasoning, and Inference" by Judea Pearl. Early on, he states that the development assumes that there are no certain entailments, no 1 or 0 probabilities -- ...
2
votes
3answers
87 views

Can two linear regression variables be perfectly correlated but not share a single causal chain ancestor?

A causal chain lists event (or fact) $y$ with all its causal antecedents. We make a model of the following form: $$ y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \epsilon $$ $\hat\beta_1$ has a p-value ...
1
vote
0answers
21 views

What are the best empirical studies comparing causal inference with experimental, quasi-experimental, and non-experimental techniques?

The Issue: People attempt to draw causal inferences using many different statistical techniques (e.g. regression, propensity score matching, regression discontinuity, instrumental variables, etc.). ...
0
votes
0answers
26 views

Necessary conditions for causality

E. Tufte writes: 'Probably the shortest true statement that can be made about causality and correlation is "Empirically observed covariation is a necessary but not sufficient condition for ...
2
votes
1answer
176 views

Does rejection of null hypothesis in multiple regression entail causation?

We make a model of the following form: $$ y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \epsilon $$ and with $n=1,000$, $\hat\beta_1$ has a p-value <0.001. If our data and data collection meets ...
0
votes
0answers
10 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 ...
0
votes
0answers
41 views

Time domain regression - determining lagged predictors

Determining lifestyle factors affecting a medical symptom I have a dataset with n=200 records corresponding to contiguous days and consisting of 1 continuous output variable (a medical symptom) and ...
0
votes
0answers
21 views

Measuring effects with longitudinal data

Problem: I have sales data through time e.g. how much each user spent on each shopping trip. I am interested in certain events (think users switching to Amazon Prime for instance). I know the date ...
3
votes
2answers
14k views

Difference between experimental data and observational data?

I'm a novice to data mining and started to read about it. What's the exact difference between experimental data and observation data? Both are obviously data; and many say observation data can lead to ...
1
vote
0answers
13 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 ...
5
votes
2answers
109 views

How does one verify causation?

After we have shown that two quantities are correlated how do we infer that the relationship is causal? And furthermore which one causes what? Now in theory one can use a "random assignment" (whatever ...
2
votes
1answer
69 views

Under what conditions does correlation imply proximity to causation?

I've recently had an experience with the whole "correlation does not imply causation", which is certainly true as far as a true/false proposition is concerned, but which also seems to be used too ...
1
vote
3answers
3k views

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 ...
1
vote
1answer
115 views

Clarification on ARDL/Unrestricted Error Correction Model

I have a few questions about unrestricted error correction models. The UECM for a model where $Y$ is the dependent variable and $x$ is the sole independent variable is given by, $$ \Delta ...
1
vote
1answer
74 views

Self Selection bias for estimating a valiable correlated to the selector

I am trying to find a way to see if a measured variable between two groups is significantly different. This would normally be done through a t-test if the two groups were randomly selected from the ...
3
votes
1answer
1k 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 ...
11
votes
5answers
14k views

Does simple linear regression imply causation?

I know correlation does not imply causation but instead the strength and direction of the relationship. Does simple linear regression imply causation? Or is an inferential (t-test, etc.) statistical ...
9
votes
1answer
510 views

How fair is it to use the word “predict” for (logistic) regression?

My understanding is that even regression does not give causality. It can only give association between y variable and x variables and possibly a direction. Am I correct? I've often found phrases ...
4
votes
1answer
263 views

Confidence interval for average treatment effect from propensity score weighting?

I am trying to estimate the average treatment effect from observational data using propensity score weighting (specifically IPTW). I think I am calculating the ATE correctly, but I don't know how to ...
0
votes
1answer
14 views

normalizing predictor by another predictor

I'm fitting a linear model with outcome $Y$. I have measurements for variables $X_1$ and $X_2$. I hypothesize that $X_1$ and $Y$ are linearly related. I want to know the slope and significance of ...
1
vote
0answers
35 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 ...
3
votes
1answer
100 views

Propensity Score can be used as a covariate in regression?

I have treated and control groups with a problem of selection in the treatment group. I am interested in the identification of the following model: $y= exp(X^\prime\beta + \alpha\cdot T)$ where $T$ ...
2
votes
2answers
146 views

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 ...
1
vote
0answers
136 views

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 ...
2
votes
0answers
42 views

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 ...
0
votes
0answers
36 views

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 ...
1
vote
1answer
97 views

Is there any correlation or causation here?

I have the following data, where 2 properties (P1 and P2) can be either True or False ...
0
votes
0answers
139 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 ...
0
votes
1answer
32 views

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 ...
10
votes
6answers
45k views

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 ...
3
votes
0answers
43 views

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, ...
3
votes
1answer
140 views

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 ...
3
votes
1answer
160 views

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 ...
5
votes
2answers
250 views

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, ...
2
votes
0answers
33 views

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 ...
15
votes
3answers
351 views

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 ...
19
votes
4answers
513 views

To what extent is the distinction between correlation and causation relevant to Google?

Context A popular question on this site is " What are common statistical sins?". One of the sins mentioned is assuming that "correlation implies causation..." link Then, in the comments with 5 ...
0
votes
0answers
43 views

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 ...