Multivariate selection can be represented as a linear transformation in a geometric framework. In this note this approach is extended to describe the effects of selection on regression analysis and to adjust for the effects of selection using the inverse of the linear transformation. (Author/BW)

Across conditions, differences between population parameters defined by common factor analysis and component analysis are demonstrated. Implications for data analytic and theoretical issues related to choice of analytic model are discussed. Results suggest that principal components analysis should not be used to obtain parameters reflecting latent…

A review of model-selection criteria is presented, suggesting their similarities. Some problems treated by hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Multivariate analysis, cluster analysis, and factor analysis are considered. (Author/GDC)

Effects of different weighting schemes on selecting the optimal number of observations in multivariate-multifacet generalizability designs are studied when cost constraints are imposed. Comparison of four schemes through simulation indicates that all four produce similar optimal values and that reliability should be similar. (SLD)