Applied Psychological Measurement

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Register here to gain access to SAGE's 500+ Journals Online

Click here for more information on The Virtual Advisor

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Free Full Text (Free PDF) Free
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 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 HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Li, Y. H.
Right arrow Articles by Lissitz, R. W
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?
Applied Psychological Measurement, Vol. 24, No. 2, 115-138 (2000)
DOI: 10.1177/01466216000242002

An Evaluation of the Accuracy of Multidimensional IRT Linking

Yuan H. Li

Prince George’s County Public Schools, Marylandjeffli{at}pgcps.org

Robert W Lissitz

University of Maryland at College Park

Most multidimensional item response theory (MIRT) parameter estimation programs solve the identification problem by requiring that multidimensional traits be distributed as multivariate normal, MVN(0, I). Three types of MIRT linking methods were evaluated, which are based on a composite transformation that changes the linked group’s reference system into the base group’s reference system: an orthogonal Procrustes rotation, a translation transformation, and a single dilation. The results indicate that the best MIRT linking method was an unbiased, effective, and consistent estimator that produced accurate estimates of transformation parameters when errors in estimation of item parameters were purposely manipulated. This method was capable of successfully recovering item parameters under model-fitting conditions.


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?


This article has been cited by other articles:


Home page
Educational and Psychological MeasurementHome page
A. A. Rupp and B. D. Zumbo
Understanding Parameter Invariance in Unidimensional IRT Models
Educational and Psychological Measurement, February 1, 2006; 66(1): 63 - 84.
[Abstract] [PDF]


Home page
Applied Psychological MeasurementHome page
Y. H. Li and W. D. Schafer
Trait Parameter Recovery Using Multidimensional Computerized Adaptive Testing in Reading and Mathematics
Applied Psychological Measurement, January 1, 2005; 29(1): 3 - 25.
[Abstract] [PDF]


Home page
Educational and Psychological MeasurementHome page
A. A. Rupp and B. D. Zumbo
A Note on How to Quantify and Report Whether Irt Parameter Invariance Holds: When Pearson Correlations are Not Enough
Educational and Psychological Measurement, August 1, 2004; 64(4): 588 - 599.
[Abstract] [PDF]