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Cyan comments on What is Bayesianism? - Less Wrong
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Evidence, as measured in log odds, has the nice property that evidence from independent sources can be combined by adding. Is there any way at all to combine p-values from independent sources? As I understand them, p-values are used to make a single binary decision to declare a theory supported or not, not to track cumulative strength of belief in a theory. They are not a measure of evidence.
There's lots of papers on combining p-values.
Well, just looking at the first result, it gives a formula for combining n p-values that as near as I can tell, lacks the property that C(p1,p2,p3) = C(C(p1,p2),p3). I suspect this is a result of unspoken assumptions that the combined p-values were obtained in a similar fashion (which I violate by trying to combine a p-value combined from two experiments with another obtained from a third experiment), which would be information not contained in the p-value itself. I am not sure of this because I did not completely follow the derivation.
But is there a particular paper I should look at that gives a good answer?
I haven't actually read any of that literature -- Cox's theorem suggests it would not be a wise investment of time. I was just Googling it for you.
Fair enough, though it probably isn't worth my time either.
Unless someone claims that they have a good general method for combining p-values, such that it does not matter where the p-values come from, or in what order they are combine, and can point me at one specific method that does all that.