“Guessing" parameter estimates for multidimensional IRT models

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Two software packages commonly used for multidimensional item response theory (IRT) models require the user to input values for the lower asymptotes of the item response functions. One way of selecting these values is to estimate lower asymptotes with a one-dimensional IRT model and use those estimates as fixed values in the multidimensional model. This procedure was compared to simply setting the asymptotes to a reasonable value. For two-factor tests, the use of unidimensional asymptotes worked well, yielding results nearly comparable to setting the lower asymptotes to the true values. With four-factor tests, in contrast, the item parameter and item response surface estimates were less accurate when the lower asymptotes were estimated through a unidimensional model. The estimates of the lower asymptotes from the unidimensional model tended to be too high for the four-factor tests, which likely caused the decreased accuracy of this procedure.

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Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.