Two versions of a decision rule for determining the most appropriate number of clusters on the basis of a correlation matrix are presented, applied, and compared with three other decision rules. The new rule is efficient for determining the number of clusters on the surface level for multilevel data. (SLD)

A Markov model for predicting performance on criterion-referenced tests is presented,. The model is expressed mathematically as a function of transition matrix, a current state vector, and a future state vector. The matrix is defined in terms of conditional probabilities, i.e., the probability of making a transition to a specific future…

The Mastery-Learning test model is extended. Methods for estimating prior probabilities are described. The use of an adjustment matrix to transform a probability of mastery measure and empirical methods for estimating adjustment matrix parameters are derived. Adjustment matrices are interpreted as indicators of instructional effectiveness and as…