Preface
Part I. The Core Ideas
1. What Makes a Difference?
1. 1 Analyzing Data in the Form of Scores
1.2 Analyzing Data in the Form of Categories
1.3 Further Reading
2. Deciding Whether Differences Are Trustworthy
2.1 Sampling Issues
2.2 Measurement Issues
2.3 The Role of Chance
2.4 Statistical Assumptions
2.5 Further Reading
3. Accounting for Differences in a Complex World
3.1 Limitations of Bivariate Analysis
3.2 The Multivariate Strategy
3.3 Common Misinterpretations of Multivariate Analyses
3.4 Further Reading
Part II. The Techniques
4. Multiple Regression
4.1 The Composite Variable in Multiple Regression
4.2 Standard Multiple Regression in Action
4.3 Trustworthiness in Regression Analysis
4.4 Accommodating Other Types of Independent Variables
4.5 Sequential Regression Analysis
4.6 Further Reading
5. Logistic Regression and Discriminant Analysis
5.1 Logistic Regression
5.2 Discriminant Analysis
5.3 Further Reading
6. Multivariate Analysis of Variance
6.1 One-Way Analysis of Variance
6.2 Factorial Analysis of Variance
6.3 Multivariate Analysis of Variance
6.4 Within-Subjects ANOVA and MANOVA
6.5 Issues of Trustworthiness in MANOVA
6.6 Analysis of Covariance
6.7 Further Reading
7. Factor Analysis
7.1 The Composite Variable in Factor Analysis
7.2 Factor Analysis in Action
7.3 Issues of Trustworthiness in Factor Analysis
7.4 Confirmatory Factor Analysis
7.5 Further Reading
8. Log-Linear Analysis
8.1 Hierarchical Log-Linear Analysis
8.2 Trustworthiness in Log-Linear Analysis
8.3 Log-Linear Analysis With a Dependent Variable: Logit Analysis
8.4 Further Reading
Bibliography
Index
About the Author