Why does the likelihood grow exactly twice? (I’m just used to really indirect evidence, which is also seldom binary in the sense that I only get to see whole suits of traits, which usually go together but in some obscure cases, vary in composition. So I guess I have plenty of C-bits that do go in B-bits that might go in A-bits, but how do I measure the change in likelihood of A given C? I know it has to do with d-separation, but if C is something directly observable, like biomass, and B is an abstraction, like species, should I not derive A (an even higher abstraction, like ‘adaptiveness of spending early years in soil’) from C? There are just so much more metrics for C than for B...)
Sorry for the ramble, I just felt stupid enough to ask anyway. If you were distracted from answering the parent, please do.
Why does the likelihood grow exactly twice? (I’m just used to really indirect evidence, which is also seldom binary in the sense that I only get to see whole suits of traits, which usually go together but in some obscure cases, vary in composition. So I guess I have plenty of C-bits that do go in B-bits that might go in A-bits, but how do I measure the change in likelihood of A given C? I know it has to do with d-separation, but if C is something directly observable, like biomass, and B is an abstraction, like species, should I not derive A (an even higher abstraction, like ‘adaptiveness of spending early years in soil’) from C? There are just so much more metrics for C than for B...) Sorry for the ramble, I just felt stupid enough to ask anyway. If you were distracted from answering the parent, please do.
I don’t understand what you’re asking, but I was wrong to say the likelihood grows by 2. See my reply to myself above.