Joint Model Selection for Location and Dispersion Effects in Unreplicated Factorial Experiments

• Activity Number: 78
• Type: Contributed
• Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Thomas Loughin*+ and Andrew Henrey
• Companies: Simon Fraser University and Simon Fraser University
• Keywords: maximum likelihood ; model averaging ; information criteria

Abstract

Most procedures that have been proposed to identify dispersion effects in unreplicated factorial designs assume that location effects have been identified correctly. Incorrect identification of location effects may impair subsequent identification of dispersion effects. We develop a model for joint identification of location and dispersion effects that can reliably identify active effects of both types. The joint model is estimated using maximum likelihood and hence effect selection is done using information-based criteria. An exhaustive search through a limited version of the space of possible models is conducted. Both a single-model output and model averaging are considered.