There was once a tribe of people isolated from the rest of the world. When they first saw white men, they thought they were the ghosts of their dead relatives, and when they first saw horses they thought they were seeing giant pigs. I don’t think scientists would do very well to put themselves in the position of these isolated tribespeople.

]]>I am wary and skeptical about the possible subjectivity of estimating prior probabilities. Yes meta-analyses have the same kind of problems. But we should be able to easily see the naked p values, if we want.

It is natural to be biased, but bias is the enemy of science, and we have to constantly watch out for it.

]]>Why only $50?

You can’t lose the bet after all.

hardnose (who you quote) is being a bit extreme– perhaps we should look at each new piece of information with the willingness to throw out whatever priors we might have.

Michelson – Morley comes to mind.

Do you consider yourself a Bayesian?

]]>I don’t see any advantage in including past evidence in a current analysis.]]>A meta-analysis will, hopefully, combine all the evidence afterwards.

Including prior probabilities is just one more way for subjectivity to enter the picture.

Agreed- I’m not describing a correct Bayesian analysis.

I’m describing a human behavior that comes from what I think is a misapplication of Bayes. ]]>

I’ve done the math.

Allow me to quote myself-

“As new evidence comes in, we can update our belief system in a mathematically correct way using Bayes assuming the data conforms to what the mathematics applies to.”

But doesn’t the mathematics assume that each piece of new information is found at random? (the bag of balls analogy)?

Perhaps I’m wrong about this– but it seems that one thing people use Bayes for is to narrow the area of investigations– they will only pick from the ‘left side’ of the bag if you will.

If I hear the ‘pro’ GMO people are paid shills 8 times, then I’m likely to restrict my search of information to people who know this-

I might be wrong about this behavior I think I see.

But I have done the math–

All things should be treated as a priori equiprobable? I’m not a statistician I’m a scientist that uses stats, and I haven’t used Bayesian analyses, honestly because it’s a PITA to get stuff published with it as a junior guy (not the best reason, but there it is). The more I’ve investigated, the more I’m convinced that priors are as subjective as you make them, and no one will accept them if they are.

“A meta-analysis will, hopefully, combine all the evidence afterwards.”

But if meta-analyses are performed with studies suffering from the problems discussed above, this will not help determine a good estimate of effect size – GIGO. Bayesian approaches have the advantage of addressing the actual problems.

Of course, there are non-Bayesian ways of addressing these problems, but meta-analyses aren’t one of them.

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