Literature DB >> 21243111

The Future of Indirect Evidence.

Bradley Efron1.   

Abstract

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. Twentieth-century statistical practice focused heavily on direct evidence, on the grounds of superior objectivity. Now, however, new scientific devices such as microarrays routinely produce enormous data sets involving thousands of related situations, where indirect evidence seems too important to ignore. 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 that allows better use of indirect evidence. This article is basically the text of a recent talk featuring some examples from current practice, with a little bit of futuristic speculation.

Entities:  

Year:  2010        PMID: 21243111      PMCID: PMC3019763          DOI: 10.1214/09-STS308

Source DB:  PubMed          Journal:  Stat Sci        ISSN: 0883-4237            Impact factor:   2.901


  5 in total

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Journal:  J Am Stat Assoc       Date:  2009-09-01       Impact factor: 5.033

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4.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.

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Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

5.  Gene expression correlates of clinical prostate cancer behavior.

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Journal:  Cancer Cell       Date:  2002-03       Impact factor: 31.743

  5 in total
  10 in total

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Review 9.  Implications of pleiotropy: challenges and opportunities for mining Big Data in biomedicine.

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  10 in total

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