JSM 2005 Online Program

Abstract #302608

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	249
Type:	Invited
Date/Time:	Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Physical and Engineering Sciences
Abstract - #302608
Title:	Efficient Designs for Conjoint Analysis and Discrete Choice Experiments
Author(s):	Rainer Schwabe*+
Companies:	Otto von Guericke University
Address:	Institute for Mathematical Stochastics, Magdeburg, International, 39016, Germany
Keywords:	conjoint analysis ; discrete choice ; paired comparisons ; optimal design ; generalized linear model ; block designs
Abstract:	In many fields such as market research, market segmentation or personnel decisions, conjoint analysis, or discrete choice experiments are performed to measure the potential decision behavior of consumers. The information will be used to judge the acceptance of potential future products in the market. The utility of such a product is determined by a variety of attributes. This utility cannot be measured directly. For discrete choice experiments, only (binary) preferences are available from a set of possible alternatives while, in linear-paired comparisons, the quantitative magnitude of the preference may be determined. Moreover, due to the complexity of the decision task, often only partial profiles are presented (i.e., the alternatives are specified by a (small) subset of attributes. For these situations, optimal or efficient designs are presented that determine the choice of the alternatives. The results are strongly related to balanced incomplete block designs and orthogonal arrays. Extensions are indicated for situations where interactions of attributes may influence the utility.

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