3 ms·
Not true. It is easy to find/construct a causal non linear relationship that won't show up in correlation tests. Correlation really isn't that great of a measur
by micro_cam 12y ago
Not true. It is easy to find/construct a causal non linear relationship that won't show up in correlation tests. Correlation really isn't that great of a measure.
- gweinberg 12y agoIt depends on what you are looking it. Exclusive or type relationships, for example, almost never show up in the natural world.
- micro_cam 12y agoDo you have a citation for that? (I work applying non parametric statistical methods to molecular disease data and i'm doubtful to say the least.)
- msellout 12y agoYou can always linearize a non-linear relationship to create a linear correlation. Even in cases such as an exclusive-or, neural networks demonstrate layering linear functions to mimic any relationship.
- micro_cam 12y agoSure but it no longer has any meaning as a significance test unless you somehow bound the complexity of the relationships you allow yourself so you're left with cross validation. Ie I can non parametrically relate any two variables.
- theophrastus 12y agoYou are correct if what you're implying is that correlation isn't a robust measure. Whereas non-correlation can be quite robust if your test isn't constructed badly (or as you imply 'constructed' badly) It's important to consider the meaning of such measures without regard to quality of the test; which can always be faulty.
- micro_cam 12y agoThat is my point exactly though I am extremely skeptical of any test for non-correlation. Gelman actually has some other articles worth reading on how dangerous it can be to make policy decisions based on such tests with real world examples including traffic laws.