Randomization in such studies is arguably a negative in practice

Re:Randomization in such studies is arguably a negative in p... by bsder on Friday April 05, 2024 @04:47PM (#39947023)

> if there's a strong model explaining it

This is the key that everybody ignores.

If you simply throw variables together, you wind up with too many confounders. You can also get the direction wrong.

"Growing tall causes you to be male" is my go to example. The correlation is super powerful--because it's completely backwards. It is also competely valid unless you have a model to differentiate--at which point it becomes obviously non-sensical.

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Re:Randomization in such studies is arguably a negative in p... by mquander on Friday April 05, 2024 @07:13PM (#39948394)

If you ran an RCT where you could directly make people to be male and then see what happened to them, you wouldn't need any further modelling to distinguish between which is causing which. The reason you need the model is if you can't randomize.

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