Statistics and Data Science Seminar
Wei Zheng, PhD candidate
MSCS, UIC
Crossover Designs under Random Subject Effects
Abstract: The statistical optimality and efficiency of crossover designs for the purpose of comparing several test treatments with a control treatment when the subject effects are random depend heavily on the unknown ratio theta of the variance of subject effects and the error variance. However, it is proved that if the class of competing designs contains a totally balanced test-control incomplete crossover designs (TBTCI), as defined by Hedayat and Yang (2005), then this TBTCI design is simultaneously A- and MV-optimal for all values of theta. This result is essentially a generalization of a result in Hedayat and Yang (2005) since their statistical model is based on fixed subject effects, where the Fisher information matrix would be identical to that of random subject effect model when theta goes to infinity. Partial works on the construction of the designs are carried out.
Wednesday April 29, 2009 at 4:15 PM in SEO 612