Empirical Bayes methods are shown to provide a practical alternative to standard least squares methods in fitting high dimensional models to sparse data. An example concerning prediction bias in educational testing is presented as an illustration. (Author)

Methods for examining the viability of assumptions underlying generalized linear models are considered. By appealing to the likelihood, a natural generalization of the raw residual plot for normal theory models is derived and is applied to investigating potential misspecification of the linear predictor. A smooth version of the plot is also…

Results are described for the first two phases of a study to develop and evaluate models of student progress in a technical training course being offered in a computer managed instructional environment at Lowry Air Force Base, Colorado. Several categories of models were developed in Phase I and defined by model type and by the type of variables…