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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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 ...
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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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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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799 views

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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382 views

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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650 views

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, ...
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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 ...
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585 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 ...
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725 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 ...
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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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158 views

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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756 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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175 views

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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2k views

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? ...
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470 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 ...
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115 views

Reporting non-causal relationships

What is the appropriate way of reporting significant regression coefficients of a multiple regression when all variables have been obtained at the same measurement occasion? Specifically, do I imply a ...
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1k views

Correlation versus cause-effect regression

I know correlation does not imply causation. I have read it nth time. (i.e. weight does not cause height etc. etc.) However, to find the effect of a moderator variable on X-Y relationship, a ...
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69 views

Time series with same variables but different respondents

I would like to measure the impact of an intervention using a form of time series or some related technique (like segmented regression). I would like to use the Schools and Staffing Survey, which ...
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1answer
228 views

Is goodness of fit needed for regression models when interpreted causally?

I'm investigating associations between socioeconomic factors and dichotomous outcome. I use generalised linear models (GLM) with log link for Bernoulli family, i.e., modelling the prevalence ratio. At ...
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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 ...
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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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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 ...
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126 views

Whats on the causal path?

I have an experiment that perturbs variable x and causes a change in variable z. There is a concurrent change in variable y. How can I determine whether variable y is on the causal path between x and ...
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243 views

Whether to use structural equation modelling to analyse observational studies in psychology

I've noticed this issue coming up a lot in statistical consulting settings and i was keen to get your thoughts. Context I often speak to research students that have conducted a study approximately ...
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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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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 ...
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1k views

How to test whether correlation measures differ when controlling or not for a third variable?

If the correlation between demographic dissimilarity and satisfaction is $r=.-14$ and the partial correlation, with career development partialled out, between demographic dissimilarity and ...
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How are propensity scores different from adding covariates in a regression, and when are they preferred to the latter?

I admit I'm relatively new to propensity scores and causal analysis. One thing that's not obvious to me as a newcomer is how the "balancing" using propensity scores is mathematically different from ...
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762 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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512 views

Can causality be inferred in a study with an experience followed by two sets of measures

I came across this study as part of a mock exam paper and was confused to say the least. Context: The study investigates cognitive and behavioural factor related to the experience of anxiety in MRI ...
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What's the relation between hierarchical models, neural networks, graphical models, bayesian networks?

They all seem to represent random variables by the nodes and (in)dependence via the (possibly directed) edges. I'm esp interested in a bayesian's point-of-view.
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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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Can cross validation be used for causal inference?

In all contexts I am familiar with cross-validation it is solely used with the goal of increasing predictive accuracy. Can the logic of cross validation be extended in estimating the unbiased ...
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114 views

Model suggestion

Could anyone give me hints as to a model framework that can be used in the following setting: The outcome A is dichotomous. I want to investigate the effect of a continuous variable B and a ...
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From a statistical perspective, can one infer causality using propensity scores with an observational study?

Question: From the standpoint of statistician (or a practitioner), can one infer causality using propensity scores with an observational study (not an experiment)? Please, do not want to start a ...
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Can I use Synthetic Control Method for Comparative Case Studies with survey data?

I'd like to assess the impact of an upcoming policy implementation, as measured by changes in questionnaire response to a Likert-scale question. I understand I could use a difference-in-difference ...
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457 views

How much can the “pyramid of evidence” be applied to economics and political sciences?

When trying to assess a validity of a claim relying on statistics, I was taught (in the school of epidemiology) that the scale to use is “the pyramid of evidence“ However, when conducting a ...
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591 views

How to test for causation in a static panel data model with small t?

I have a static panel data model with small T (T=5) that makes it impossible for me to use granger causality as it requires a long time span. So my question: Is there any alternative solution to ...
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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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Under what conditions does correlation imply causation?

We all know the mantra "correlation does not imply causation" which is drummed into all first year statistics students. There are some nice examples here to illustrate the idea. But sometimes ...