Detection of Mutually Dependent Test Items Using the LCI Test

  • Takamitsu Hashimoto
  • Maomi Ueno
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6797)


Item response theory (IRT) is widely used for test analyses. Most models of IRT assume local independence, meaning that when the ability variables influencing the test performance are held constant, an examinee’s responses to any pair of items are statistically independent. However, many factors might cause local dependence among items. Consequently, conditional independence (CI) tests are needed among items given a latent ability variable. Hashimoto and Ueno (2011) proposed the latent conditional independence (LCI) test. While other CI tests are sensitive to dependencies of items aside from the targets, the LCI test is robust to such dependencies. However, when the two target items affect the same items, the LCI test might fail to detect local independency between the targets. The previous work of Hashimoto and Ueno (2011) is improved on to obtain a more accurate detection method.


latent variable conditional independence test Bayesian network IRT 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Takamitsu Hashimoto
    • 1
    • 2
  • Maomi Ueno
    • 1
  1. 1.University of Electro-CommunicationsChofu-shiJapan
  2. 2.National Center for University Entrance ExaminationsMeguro-kuJapan

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