When using linear models for cluster-correlated or longitudinal data, a common modeling practice is to begin by fitting a relatively simple model and then to increase the model complexity in steps. New predictors might be added to the model, or a more complex covariance structure might be specified for the observations. When fitting models for…

The intent of this paper is to generalize the min and max clustering procedures in such a way that the assumption of a symmetric similarity measure is unnecessary. (Author)

Several methods for the analysis of three-way data (data classified three ways) are described and shown to be variants of principal components analysis of the two-way supermatrix in which each two-way slice is strung out into a column vector. Direct fitting and fitting derived data are considered. (SLD)

A modification index is presented to aid in reformulating hypothetical models rejected after analysis of empirical data. This index is an improvement over the one in the LISREL V computer program in that it takes into account changes in all parameters of the model when one parameter is freed. (SLD)

A method for detecting instructional sensitivity (item bias) in test items is proposed. This method extends item response theory by allowing for item-specific variation in measurement relations across students' varying instructional backgrounds. Item bias detection is a by-product. Traditional and new methods are compared. (SLD)