A new method was developed to assist in the selection of a test length by utilizing computer simulation procedures and item response theory. A demonstration of the method presents results which address the influences of item pool heterogeneity matched to the objectives of interest and the method of item selection. (Author/PN)

The impact of capitalizing on chance in item selection on the accuracy of test information functions was studied through simulation, focusing on examinee sample size in item calibration and the ratio of item bank size to test length. (SLD)

Item parameter estimation errors in test development are highlighted. The problem is illustrated with several simulated data sets, and a conservative solution is offered for addressing the problem in item response theory test development practice. Steps that reduce the problem of capitalizing on chance in item selections are suggested. (SLD)

Errors in item parameter estimates have a negative impact on the accuracy of item and test information functions. The estimation errors may be random, but because items with higher levels of discriminating power are more likely to be selected for a test, and these items are most apt to contain positive errors, the result is that item information…

Addressing the shortcomings of classical item statistics for selecting criterion-referenced test items, this paper describes an optimal item selection procedure utilizing item response theory (IRT) and offers examples in which random selection and optimal item selection methods are compared. Theoretical advantages of optimal selection based upon…

A brief overview of item response theory is provided, and a 186-item bibliography of books and articles on the subject dating from 1953 to June 1989 is presented. The overview includes a definition of the theory, a discussion of its development and application, and comparisons with classical test theory. All publications in the bibliography were…

Item response model applications to National Assessment of Educational Progress (NAEP) data specifically aimed at the uses of item response models in mathematics item banking are discussed. Approaches for addressing goodness of fit were organized into three categories: Checks on model assumptions, expected features, and additional model…