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Local Dependence Diagnostics in IRT Modeling of Binary Data

Local dependence (LD) for binary IRT models can be diagnosed using Chen and Thissen’s bivariate X2 statistic and the score test statistics proposed by Glas and Suárez-Falcón, and Liu and Thissen. Alternatively, LD can be assessed using general purpose statistics such as bivariate residuals or Maydeu-Olivares and Joe’s Mr statistic. The authors introduce a new general statistic for assessing the source of model misfit, R2, and compare its performance to the above statistics using a simulation study. Results suggest that the bivariate and trivariate X2 statistics have unacceptable Type I error rates. As for the remaining statistics, if their computation involves the information matrix (bivariate residuals and score tests), they show good power; if not (Mr and R2), they lack power. Of course, the performance of the bivariate residuals and score tests depends on how the information matrix is approximated.

Posted in: Journal Article Abstracts on 08/17/2012 | Link to this post on IFP |
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