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Thanks. Assuming they refer to the exact same phenomenon, I agree that ommitted variable bias is better terminology. I wonder why Wikipedia has separate entrie
by monoideism 6y ago
Thanks. Assuming they refer to the exact same phenomenon, I agree that ommitted variable bias is better terminology.
I wonder why Wikipedia has separate entries for them:
https://en.wikipedia.org/wiki/Omitted-variable_bias https://en.wikipedia.org/wiki/Omitted-variable_bias
https://en.wikipedia.org/wiki/Confounding https://en.wikipedia.org/wiki/Confounding
- rmrfstar 6y agoContext. The picture at the top of the confounding article gives it away. Those kinds of diagrams are common in "hierarchical Bayesian models" like LDA. In the simple linear setting, they are the same thing. Teaching people the "confounding variable" concept in a general setting before teaching them about "omitted variable" in a linear setting is like teaching people about Riemannian manifolds before teaching them about vector spaces. Correlation isn't a particularly useful concept outside of simple linear models.