The statistical analysis of processing tree models is advanced by showing how the parameters of estimation and hypothesis testing, based on the likelihood functions, can be accomplished by adapting the expectation-maximization (EM) algorithm. The adaptation makes it easy to program a personal computer to accomplish the stages of statistical…

This study examined the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric,…

The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…