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Abstract:
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Familiar statistical tests and estimates are obtained by the direct observation of cases of interest. A clinical trial of a new drug, for instance, will compare the drug's effects on a relevant set of patients and controls. Sometimes, though, "indirect evidence" may be temptingly available, perhaps the results of previous trials on closely related drugs. Very roughly speaking, the difference between direct and indirect statistical evidence marks the boundary between frequentist and Bayesian thinking. New scientific devices routinely produce enormous data sets involving thousands of related situations. Empirical Bayes methodology offers an attractive direct/indirect compromise. There is already some evidence of a shift toward a less rigid standard of statistical objectivity. This talk mainly consists of examples from current practice, with a bit of futuristic speculation.
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