Item Parameter Estimation for a Continuous Response Model Using an EM Algorithm

Abstract

An item parameter estimation procedure is cedure was pro-developed using an EM algorithm for Samejima's (1973) continuous item response model. The potential usefulness of this model is examined, including the density function and the practical meaning of the item parameters and statistical properties of the model. The expected a posteriori and maximum likelihood estimates of the person (0) parameters and their associated standard errors are also described. The item parameter estimation pro grammed and evaluated using simulated data. The results show that the estimation procedure performs well in estimating item and 0 parameters. These estimation procedures should permit the application of the continuous response model to many measurement problems.

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