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  • http://hdl.handle.net/10402/era.24836
  • Controlling IER, EER, and FDR In Replicated Regular Two-Level Factorial Designs
  • Akinlawon, Oludotun J
  • English
  • individual error rate
    experimentwise error rate
    false discovery rate
    replicated factorial experiments
  • Dec 20, 2011 9:05 AM
  • Thesis
  • English
  • Adobe PDF
  • 352251 bytes
  • 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.
  • Master's
  • Master of Science
  • Department of Mathematical and Statistical Sciences
  • Statistics
  • Spring 2012
  • Li, Pengfei (Mathematical and Statistical Sciences)
    Karunamuni, Rohana (Mathematical and Statistical Sciences)
  • Yuan, Yan (Public Health)
    Zhang, Peng (Mathematical and Statistical Sciences)