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Rebecca Barter - Confounding in causal inference: what is it, and what to do about it?

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Often in science we want to be able to quantify the effect of an action on some outcome. For example, perhaps we are interested in estimating the effect of a drug on blood pressure. While it is easy to show whether or not taking the drug is associated with an increase in blood pressure, it is surprisingly difficult to show that taking the drug actually caused an increase (or decrease) in blood pressure. Causal inference is the field of statistics (or economics, depending on who you ask) that is concerned with estimating the causal effect of a treatment.[^check] Why is estimating a causal effect difficult? To put it simply, the fundamental problem is that we can never actually observe a causal effect. The causal effect is defined to be the difference between the outcome when the treatment was applied and the outcome when it was not. This difference is a fundamentally unobservable quantity. For any individual, we can only ever observe their blood pressure either in the situation (1) when

Confounding in causal inference: what is it, and what to do about it? – Rebecca Barter Often in science we want to be able to quantify the effect of an action on some outcome. For example, perhaps we are interested in estimating the effect of a drug on blood pressure. While it is easy to show whether or not taking the drug is associated with an increase in blood pressure, it is surprisingly difficult to show that taking the drug actually caused an increase (or decrease) in blood pressure. Causal inference is the field of statistics (or economics, depending on who you ask) that is concerned wit

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Rebecca Barter - Confounding in causal inference: what is it, and what to do about it?

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