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Controlling IER, EER, and FDR In Replicated Regular Two-Level Factorial Designs

  • Author / Creator
    Akinlawon, Oludotun J
  • Replicated regular two-level factorial experiments are very useful for industry. The basic purpose of this type of experiments is to identify active effects that affect the mean and variance of the response. Hypothesis testing procedures are widely used for this purpose. However, the existing methods give results that are either too liberal or too conservative in controlling the individual and experimentwise error rates (IER and EER respectively). In this thesis, we propose a resampling procedure and an exact-variance method for identifying active effects for the mean and variance of the response, respectively. Monte Carlo studies show that our proposed methods perform extremely well in terms of controlling the IER and EER. We also extend our proposed methods to control the false discovery rate. Two real data sets were used as case study to illustrate the performance of the proposed methods.

  • Subjects / Keywords
  • Graduation date
    2012-06
  • Type of Item
    Thesis
  • Degree
    Master of Science
  • DOI
    https://doi.org/10.7939/R3ZD93
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Master's
  • Department
    • Department of Mathematical and Statistical Sciences
  • Specialization
    • Statistics
  • Supervisor / co-supervisor and their department(s)
    • Karunamuni, Rohana (Mathematical and Statistical Sciences)
    • Li, Pengfei (Mathematical and Statistical Sciences)
  • Examining committee members and their departments
    • Yuan, Yan (Public Health)
    • Zhang, Peng (Mathematical and Statistical Sciences)