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Journal of Educational Measurement

Published on behalf of the National Council on Measurement in Education

Edited by:
James E. Carlson


ISI Journal Citation Reports® Ranking: 2008: 47/61 Psychology, Applied; 31/42 Psychology, Educational; 9/11 Psychology, Mathematical
Impact Factor: 0.694


The Journal of Educational Measurement (JEM) publishes original measurement research, provides reviews of measurement publications, and reports on innovative measurement applications. The topics addressed will interest those concerned with the practice of measurement in field settings, as well as be of interest to measurement theorists. In addition to presenting new contributions to measurement theory and practice, JEM also serves as a vehicle for improving educational measurement applications in a variety of settings.

TopNews and Announcements

Online production tracking now available through Author Services!
Visit the Author Services website for a wealth of information for all authors plus online production tracking for your article. Authors of articles already accepted for publication in the Journal of Educational Measurement can register to:

  • track the status of their article online as it moves through Blackwell's production process
  • choose to receive e-mail alerts on article status, from copyediting and typesetting through the printing process
  • get free access to their article when it is published online

In addition, all authors visiting the site who are interested in submitting articles can access information and tips on:

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  • Electronic artwork details
  • And more features added over time!

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TopHighlights

  • A Domain-level Approach to Describing Growth in Achievement
    E. Matthew Schulz, Won-Chan Lee, and Ken Mullen (42:1)
  • Measuring the Benefits of Examinee-Selected Questions.
    Nancy L. Allen, Paul W. Holland, and Dorothy T. Thayer (42:1)
  • A Mixture Model Analysis of Differential Item Functioning
    Allan S. Cohen and Daniel M. Bolt (42:2)
  • The Performance of a Method for the Long-term Equating of Mixed-Format Assessment
    Akihito Kamata and Richard Tate (42:2)
  • A Bayesian Method for Evaluating Passing Scores: The PPoP Curve
    Howard Wainer, X. A. Wang, William P Skorupski, and Eric T. Bradlow (42:3)
  • A Comparison of Item-Selection Methods for Adaptive Tests with Content Constraints
    Wim J. van der Linden (42:3)