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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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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222 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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2answers
6k 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 ...
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3answers
125 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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238 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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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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1answer
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How can I represent Conditional Probability Table based Bayesian Networks in Winbugs? [closed]

Greetings, Winbugs seem to support either stochastic or deterministic relationship between variables. However, many Bayesian Networks represent relationships between variables using conditional ...
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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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7answers
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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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3answers
111 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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4answers
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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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1answer
1k views

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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387 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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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 ...