Noted for its breadth and depth of coverage of multivariate statistics and its emphasis on power, this classic text focuses on a conceptual understanding of the material rather than on proving results. Numerous examples, along with use of SAS and SPSS, indicate what the numbers mean and how to interpret the results.
Noted for its breadth and depth of coverage of multivariate statistics and its emphasis on power, this classic text focuses on a conceptual understanding of the material rather than on proving results. Numerous examples, along with use of SAS and SPSS, indicate what the numbers mean and how to interpret the results.
Keenan Pituch is Associate Professor in the Quantitative Methods Area of the Department of Educational Psychology at the University of Texas at Austin. James P Stevens is Professor Emeritus at University of Cincinatti.
Inhaltsangabe
1. Introduction 2. Matrix Algebra 3. Multiple Regression for Prediction 4. Two-Group Multivariate Analysis of Variance 5. K-Group MANOVA: A Priori and Post-Hoc Procedures 6. Assumptions in MANOVA 7. Factorial ANOVA and MANOVA 8. Analysis of Covariance 9. Exploratory Factor Analysis 10. Discriminant Analysis 11. Binary Logistic Regression 12. Repeated-Measures Analysis 13. Hierarchical Linear Modeling 14. Multivariate Multilevel Modeling 15. Canonical Correlation 16. Structural Equation Modeling Appendix A: Statistical Tables Appendix B: Obtaining Nonorthogonal Contrasts in Repeated Measures Design Answers to Half of the Text problems