Abstract
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.
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Hashimoto, T., Ueno, M. (2011). Detection of Mutually Dependent Test Items Using the LCI Test. In: Onada, T., Bekki, D., McCready, E. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2010. Lecture Notes in Computer Science(), vol 6797. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25655-4_18
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DOI: https://doi.org/10.1007/978-3-642-25655-4_18
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