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Science for Subjectivists

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I read this fascinating paper by Greg Gandenberger . It's an argument to the effect that one can give a good Bayesian rationale for, in some circumstances, paying attention to stopping rules. These are rules for data collection, in particular rules which tell you when you have gathered enough data and should stop gathering more. One might compare (and Greg does compare) rules which tell you to stop after some fixed point - say, after one has performed the test on 300 subjects - versus rules which say something like `Keep going until you either run out of money or your data supports your favourite hypothesis to some given degree.' Classical statisticians typically say that for epistemic reasons one needs to pay attention to these rules, whereas Bayesian statisticians argue that one very often need not pay any attention to them (in these cases they are "noninformative"). GG is here to argue that there is a particular class of cases where Bayesians will indeed say you n