An item sampling model for achievement testing with items scored in an arbitrary number of categories is investigated. (Author)

The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. The measurement model categorizes items according to the cells of a table of test specifications, and the linear function derived for minimizing error variance in prediction uses responses to these categories. (Author/JKS)

Empirical results are presented as regards the implementation of a latent-trait psychometric model by means of conditional maximum likelihood estimation. Items are scored polychotomously into varying numbers of nominal categories and the test and item characteristic curves and information functions are examined. It is concluded that scoring items…

A tailored testing model employing the beta distribution, whose mean equals the difficulty of an item and whose variance is approximately equal to the sampling variance of the item difficulty, and employing conditional item difficulties, is proposed. The model provides a procedure by which a minimum number of items of a test, consisting of a set…

A linear regression model was used to select items from a pool of 700 arithmetic word problems to be used in a computer-assisted mathematics curriculum for elementary school students. The experimental procedure first involved a stepwise linear regression analysis of a student's performance over a set of 25 problems. The probability correct for…