Abstract #300567

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JSM 2003 Abstract #300567
Activity Number: 320
Type: Topic Contributed
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Stat. Sciences
Abstract - #300567
Title: Model Choice Applied to Consumer Preferences
Author(s): Iain B. Pardoe*+
Companies: Lundquist College of Business
Address: 1208 University of Oregon, Eugene, OR, 97403-1205,
Keywords: Bayesian methodology ; diagnostic ; graphical method ; mixture models ; model assessment ; random effects
Abstract:

Standard model assessment techniques such as residual plots or Akaike's information criterion can be difficult to use or provide limited insight into model fit when applied in nonstandard regression contexts such as random effects or mixture models. This paper considers the application of Bayesian ideas to model choice for a large consumer preference dataset where nonstandard models appear to be needed but it is unclear which model is most appropriate. In addition, it is shown that suitably chosen graphical methods can provide insights into not only which of a set of competing models is most useful, but also how model results can best be interpreted.

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