Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here for FREE ACCESS to this landmark database

Click here for more information on The Virtual Advisor

Sign In to gain access to subscriptions and/or personal tools.
Applied Psychological Measurement
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via ISI Web of Science (3)
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by DeSarbo, W. S.
Right arrow Articles by Hollman, F. G.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Modeling Dynamic Effects in Repeated-Measures Experiments Involving Preference/Choice: An Illustration Involving Stated Preference Analysis

Wayne S. DeSarbo

Pennsylvania State University

Donald R. Lehmann

Columbia University

Frances Galliano Hollman

Pennsylvania State University

Preference structures that underlie survey orexperimental responses may systematically varyduring the administration of such measurement.Maturation, learning, fatigue, and responsestrategy shifts may all affect the sequentialelicitation of respondent preferences at differentpoints in the survey or experiment. Theconsequence of this phenomenon is that responsesand effects can vary systematically within the dataset. To capture these structural changes, the authorspresent a maximum likelihood–based change-pointmultiple regression methodology that explicitlydetects discrete structural changes at various pointsin time/sequence in regression coefficients bysimultaneously estimating the number of changepoints, their location and duration in the sequenceof data points, and the respective regressioncoefficients for each subset of the data defined bythe change points. An application involving astated preference or conjoint analyses study ofstudent apartment choices illustratesthat the structure of preferences changessignificantly over the sequence of profileresponses.

Key Words: preference/choice experiments • behavioral decision making • maximum likelihood estimation • models of structural change • conjoint analysis • consumer psychology

Applied Psychological Measurement, Vol. 28, No. 3, 186-209 (2004)
DOI: 10.1177/0146621604264150
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?