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

  • Replicated factorial experiments
  • False discovery rate
  • Individual error rate
  • Experimentwise error rate

• Graduation date

  Spring 2012

• 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.