How Confounding Was Defined?

Before talking about how confounding should be defined, let’s talked about how it was defined before. Some declarative defintions A confounder is any variable that is correlated with both X and Y. A confounder X and Y is a variable Z that is (1) associated with X in the population at large, and (2) associated …

How Randomized Controlled Trial Deconfounds the Confounding Bias

What is confunding bias? Imagine you are a farmer trying to determine applying fertilizer A to the field will increase the yield of crops. In other words, you are trying to establish a causal relationship between fertilizer A and yield. Our tricky Nature tells you that the effect of the fertilizer is mixed with a …

Causal Diagram and Bayesian Network (Part 2)

There are three building blocks of Baysian Network. Remember that a Bayesian Network is nothing but some arrows connecting with different nodes representing the conditional probability table. The so-called building blocks are just the three types of arrow patterns. Arrow Pattern Easy To RMB Name Description A –> B –> C Chain Fire -> Smoke …

Causal Diagram and Bayesian Network (Part 1)

After looking at how statistics pay little attention on causation compared with correlation, the author talks about Bayesian Network, in which he is one of the main contributors, and its relation with causal diagram. Bayes Theorem and Inverse Probability Bayes theorem provides a mathematical description of two events, the hypothesis (D) occurring before the evidence …

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