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Efficient Full Information Maximum Likelihood Estimation for Multidimensional IRT Models IRT

Rijmen, Frank
Publication Year:
Report Number:
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Item Response Theory (IRT), Marginal Maximum Likelihood Estimation, Estimation (Mathematics), Graphical modeling (Statistics)


In this paper, it is shown how the approach of Gibbons and Hedeker (1992) can be placed into a graphical framework. The advantage of the graphical model framework is that efficient estimation schemes can be derived in a fully automatic way by applying algorithms to the graphical representation of a statistical model. This renders the approach fairly generally applicable, and tedious derivations by hand are no longer involved. The generality of the approach is demonstrated by applying it to a multidimensional IRT model with a second order dimension. It turns out that full information maximum likelihood estimation for such a model also requires the evaluation of two-dimensional integrals only.

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