Estimating the standard error of the maximum likelihood ability estimator in adaptive testing using the posterior-weighted test information function

摘要

The standard error of the maximum likelihood ability estimator is commonly estimated by evaluating the test information function at an examinee's current maximum likelihood estimate (a point estimate) of ability. Because the test information function evaluated at the point estimate may differ from the test information function evaluated at an examinee's true ability value, the estimated standard error may be biased under certain conditions. This is of particular concern in adaptive testing because the height of the test information function is expected to be higher at the current estimate of ability than at the actual value of ability. This article proposes using the posterior-weighted test information function in computing the standard error of the maximum likelihood ability estimator for adaptive test sessions. A simulation study showed that the proposed approach provides standard error estimates that are less biased and more efficient than those provided by the traditional point estimate approach.