This volume presents the important concepts required for implementing two disciplines of factor analysis - exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) with an emphasis on EFA/CFA linkages. Modern extensions of older data analysis methods (e.g., ANOVA, regression, MANOVA, and descriptive discriminant analysis) have brought theory-testing procedures to the analytic forefront. Variations of factor analysis, such as the factoring of people or time, have great potential to inform psychological research. Thompson deftly presents highly technical material in an appealing and accessible manner. The book is unique in that it presents both exploratory and confirmatory methods within the single category of the general linear model (GLM). Canons of best factor analytic practice are presented and explained. An actual data set, generated by 100 graduate students and 100 faculty from the United States and Canada, is used throughout the book, allowing readers to replicate reported results and explore variations on reported analyses. Different combinations of these variables and participants are used to illustrate EFA and CFA applications. The book also includes a glossary, a notation summary, and various SPSS syntax files that readers may use to implement elegant factor analytic solutions. Instructors or students who seek a clear and concise text about factor analysis will find this book to be an invaluable resource.