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Some Aspects of Bayesian Multiple Testing

Herath, Gonagala Mudiyanselage Nilupika

Abstract Details

2021, PhD, University of Cincinnati, Arts and Sciences: Mathematical Sciences.
Multiple testing in statistics refers to carrying out several statistical tests simultaneously. As the number of tests increases, the probability of incorrectly rejecting the null hypothesis also increases (multiplicity problem). Therefore, some multiplicity adjustment should always be considered to control the error rate. Making decisions without multiplicity adjustment can lead to error rates that are higher than the nominal rate. While several approaches to multiplicity adjustment are available, the Bayesian method is the only approach that inherently adjusts for multiplicity. This thesis considers the Bayesian approach to the multiple testing problem for different types of data: continuous and discrete data.
Sival Sivaganesan|, Ph.D (Committee Chair)
Xia Wang, Ph.D (Committee Member)
Hang Joon Kim, Ph.D (Committee Member)
Seongho| Song, Ph.D (Committee Member)
131 p.

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Citations

  • Herath, G. M. N. (2021). Some Aspects of Bayesian Multiple Testing [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1637060945128901

    APA Style (7th edition)

  • Herath, Gonagala Mudiyanselage Nilupika. Some Aspects of Bayesian Multiple Testing. 2021. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1637060945128901.

    MLA Style (8th edition)

  • Herath, Gonagala Mudiyanselage Nilupika. "Some Aspects of Bayesian Multiple Testing." Doctoral dissertation, University of Cincinnati, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1637060945128901

    Chicago Manual of Style (17th edition)