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IMST 2008 / FIM XVI

Decision theoretic Bayesian hypothesis testing with focus on skewed alternatives. By Naveen K. Bansal Ru Sheng Marquette University Milwaukee, WI 53051 Email: naveen.bansal@mu.edu http://www.mscs.mu.edu/~naveen/. IMST 2008 / FIM XVI. Directional Error (Type III error):

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IMST 2008 / FIM XVI

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  1. Decision theoretic Bayesian hypothesis testing with focus on skewed alternatives By Naveen K. Bansal RuSheng Marquette University Milwaukee, WI 53051 Email: naveen.bansal@mu.edu http://www.mscs.mu.edu/~naveen/ IMST 2008 / FIM XVI

  2. Directional Error (Type III error): Sarkar and Zhou (2008, JSPI) Shaffer (2002, Psychological Methods) Finner ( 1999, AS) Lehmann (1952, AMS; 1957, AMS) Main points of these work is that if the objective is to find the true Direction of the alternative after rejecting the null, then a Type III error must be also controlled. Type III error is defined as P( false directional error if the null is rejected). The traditional method does not control the directional error. For example, IMST 2008 / FIM XVI

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  4. Bayes Rule Bayes Rule IMST 2008 / FIM XVI

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  6. Relationship with the False Discovery Rates IMST 2008 / FIM XVI

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  8. An Application: An experiment was conducted to see the effect of a sequence knockdown from non-coding genes. Hypothesis was that this knockdown will cause the overexpression of the mRNAs of the coding genes. The implication of this is that this will shows how the non-coding genes interact with coding genes. In other words, non-coding genes also play a part in protein synthesis. Here it can be assumed that that the effect of knockdown on the coding genes (if there is any) would be mostly overexpression of mRNAs than underexpression of mRNAs. The objective would be to detect as many of overexpressed genes as possible. IMST 2008 / FIM XVI

  9. Table 1 Possible outcomes from hypothesis tests IMST 2008 / FIM XVI

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  11. This theorem and our previous discussion on the Bayes decision rule implies that under the independent hypotheses testing setting, the Bayes rule obtained from a single test problem which minimizes the average expected false discoveries, can be used under multiple hypotheses problem. The false discovery rates of this procedure can be obtained by computing the posterior probabilities. The prior probabilities will determine whether the positive hypothesis or the negative hypothesis will be more frequently correctly detected. IMST 2008 / FIM XVI

  12. Computation of Bayes Rule: IMST 2008 / FIM XVI

  13. Choice of the loss function: IMST 2008 / FIM XVI

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  17. Power Comparison: IMST 2008 / FIM XVI

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  20. Another Approach: IMST 2008 / FIM XVI

  21. Power Comparison of a skew-normal Bayes with the UMP test IMST 2008 / FIM XVI

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