Regression Analysis for Social Sciences
- Alexander von Eye, Michigan State University, East Lansing, U.S.A.
- Christof Schuster, University of Michigan, Ann Arbor, U.S.A.
Regression Analysis for Social Sciences presents methods of regression analysis in an accessible way, with each method having illustrations and examples. A broad spectrum of methods are included: multiple categorical predictors, methods for curvilinear regression, and methods for symmetric regression. This book can be used for courses in regression analysis at the advanced undergraduate and beginning graduate level in the social and behavioral sciences. Most of the techniques are explained step-by-step enabling students and researchers to analyze their own data. Examples include data from the social and behavioral sciences as well as biology, making the book useful for readers with biological and biometrical backgrounds. Sample command and result files for SYSTAT are included in the text.
Academics, researchers, and students in the social sciences including psychology and sociology.