Basics of Structural Equation Modeling

My interest in what happens in diverse urban schools began when I became involved in a study of school desegregation while in graduate school. Those interests have led me to study a range of issues in schools, including school schedules and structures, teaching approaches such as cooperative learning and conflict resolution, social influence processes, and student background characteristics including poverty, type of housing, language, ability, and race/ethnicity. This work has been facilitated by time I spent in the Saint Paul Public Schools as their director of research, evaluation and assessment. Recently, my work has moved beyond schools to look more broadly at how universities engage urban communities to build partnerships addressing key social issues. I have complemented my substantive interests with methodology interests in structural equation methods and program evaluation. Finally, I have held administrative roles that have enriched and informed my research interests, including director of the Center for Applied Research and Educational Improvement (CAREI), assistant/associate vice president for multicultural and academic affairs, and now vice president for system academic administration . I am a past-president of the Society for the Psychological Study of Social Issues (SPSSI), and currently edit one of their journals, Analyses of Social Issues and Public Policy.

PART ONE: BACKGROUND What Does It Mean to Model Hypothesized Causal Processes with Nonexperimental Data? History and Logic of Structural Equation Modeling PART TWO: BASIC APPROACHES TO MODELING WITH SINGLE OBSERVED MEASURES OF THEORETICAL VARIABLES The Basics Path Analysis and Partitioning of Variance Effects of Collinearity on Regression and Path Analysis Effects of Random and Nonrandom Error on Path Models Recursive and Longitudinal Models Where Causality Goes in More Than One Direction and Where Data Are Collected Over Time PART THREE: FACTOR ANALYSIS AND PATH MODELING Introducing the Logic of Factor Analysis and Multiple Indicators to Path Modeling PART FOUR: LATENT VARIABLE STRUCTURAL EQUATION MODELS Putting It All Together Latent Variable Structural Equation Modeling Using Latent Variable Structural Equation Modeling to Examine Plausability of Models Logic of Alternative Models and Significance Tests Variations on the Basic Latent Variable Structural Equation Model Wrapping up

"Overall, the book is a well-written introduction to structural equation modelling for people with a non-mathematical background. The stress is put on the logic of structural equation modelling and therefore it might be appreciated by more mathematical trained statisticians as well." -- Oliver Thas * The Statistician * "This book is a gentle introduction to the topic of structural equation modelling." -- Richard A. Chechile