Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here for FREE ACCESS to this landmark database

Click here to sign up for SAGE Journal Email Alerts today!

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
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in 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 Web of Science (1)
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Stark, S.
Right arrow Articles by Drasgow, F.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

An IRT Approach to Constructing and Scoring Pairwise Preference Items Involving Stimuli on Different Dimensions: The Multi-Unidimensional Pairwise-Preference Model

Stephen Stark

University of South Florida, sstark{at}cas.usf.edu

Oleksandr S. Chernyshenko

University of Canterbury, New Zealand

Fritz Drasgow

University of Illinois at Urbana-Champaign

This article proposes an item response theory (IRT) approach to constructing and scoring multidimensional pairwise preference items. Individual statements are administered and calibrated using a unidimensional single-stimulus model. Tests are created by combining multidimensional items with a small number of unidimensional pairings needed to identify the latent metric. Trait scores are then obtained using a multidimensional Bayes modal estimation procedure based on a mathematical model called MUPP, which is illustrated and tested here using Monte Carlo simulations. Simulation results show that the MUPP approach to test construction and scoring provides accurate parameter recovery in both one- and two-dimensional simulations, even with relatively few (say, 15%) unidimensional pairings. The implications of these results for constructing and scoring fake-resistant personality items are discussed.

Key Words: IRT • pairwise preference • paired comparison • forced choice • ipsative • multidimensional IRT • personality assessment • faking

Applied Psychological Measurement, Vol. 29, No. 3, 184-203 (2005)
DOI: 10.1177/0146621604273988


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?