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Bayes Factors Based on Test Statistics

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  • Valen Johnson

    (University of Michigan School of Public Health)

Abstract

Traditionally, the use of Bayes factors has required the specification of proper prior distributions on model parameters implicit to both null and alternative hypotheses. In this paper, I describe an approach to defining Bayes factors based on modeling test statistics. Because the distributions of test statistics do not depend on unknown model parameters, this approach eliminates the subjectivity normally associated with the definition of Bayes factors. For standard test statistics, including the _2, F, t and z statistics, the values of Bayes factors that result from this approach can be simply expressed in closed form.

Suggested Citation

  • Valen Johnson, 2004. "Bayes Factors Based on Test Statistics," The University of Michigan Department of Biostatistics Working Paper Series 1029, Berkeley Electronic Press.
    • Handle: RePEc:bep:mchbio:1029
    Note: oai:bepress.com:umichbiostat-1029
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    File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1029&context=umichbiostat
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