Buch, Englisch, 256 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 521 g
An Intuitive Approach
Buch, Englisch, 256 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 521 g
ISBN: 978-1-4129-0915-0
Verlag: Sage Publications, Inc
Making Sense of Multivariate Data Analysis is a short introduction to multivariate data analysis (MDA) for students and practitioners in the behavioral and social sciences. It provides a conceptual overview of the foundations of MDA and of a range of specific techniques including multiple regression, logistic regression, discriminant analysis, multivariate analysis of variance, factor analysis, and log-linear analysis. As a conceptual introduction, the book assumes no prior statistical knowledge, and contains very few symbols or equations. Its primary objective is to expose the conceptual unity of MDA techniques both in their foundations and in the common analytic strategies that lie at the heart of all of the techniques. Although introductory, the book encourages the reader to reflect critically on the general strengths and limitations of MDA techniques. Each chapter includes references for further reading accessible to the beginner.
This is an ideal text for advanced undergraduate and graduate courses across the social sciences. Practitioners who need to refresh their knowledge of MDA will also find this an invaluable resource.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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