Abstract

The sensitivity of marginal maximum likelihood es timation of item and ability (θ) parameters was ex amined when the prior θ distributions are not matched to the underlying θ distributions. Thirty sets of 45-item test data were generated by specifi cation of three types of underlying θ distributions. They were then analyzed with PC-BILOG. Appropri ate specification of the prior θ distribution increased the accuracy of estimation for item and θ param eters when the sample size was large. With a small dataset, the appropriate specification of the prior increased the accuracy of θ parameter estimation, but it did not have that effect on item parameter esti mation. Only with a large dataset and matched under lying and prior θ distributions did increasing the number of quadrature points improve the accuracy of estimation of the item parameters. However, the ac curacy of θ estimation was increased by increasing the number of quadrature points, regardless of sample size and appropriateness of the prior θ distribution. The number of examinees had an im portant effect on the accuracy of item parameter estimation.

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