Making Sense of Multivariate Data Analysis

John Spicer was an Associate Professor and Head of Psychology at Massey University, New Zealand until the end of 2002, when he took early retirement to devote all of his time to writing books. Earlier, he was a Research Fellow for several years at the University of Auckland, New Zealand, and held Visiting Fellowships at the Universities of Michigan and London. His primary research interests have been in health psychology, and he has published articles mainly on cardiovascular disease and theoretical issues in a variety of international journals. He was coeditor of Social Dimensions of Health and Disease: New Zealand Perspectives (1994). Most of his undergraduate and graduate teaching has focused on research methods, particularly multivariate data analysis. In 2002 he coauthored a chapter on sociological and psychological methods in the fourth edition of the Oxford Textbook of Public Health.

• PrefacePart I. The Core Ideas1. What Makes a Difference?1. 1 Analyzing Data in the Form of Scores1.2 Analyzing Data in the Form of Categories1.3 Further Reading2. Deciding Whether Differences Are Trustworthy2.1 Sampling Issues2.2 Measurement Issues2.3 The Role of Chance2.4 Statistical Assumptions2.5 Further Reading3. Accounting for Differences in a Complex World3.1 Limitations of Bivariate Analysis3.2 The Multivariate Strategy3.3 Common Misinterpretations of Multivariate Analyses3.4 Further ReadingPart II. The Techniques4. Multiple Regression4.1 The Composite Variable in Multiple Regression4.2 Standard Multiple Regression in Action4.3 Trustworthiness in Regression Analysis4.4 Accommodating Other Types of Independent Variables4.5 Sequential Regression Analysis4.6 Further Reading5. Logistic Regression and Discriminant Analysis5.1 Logistic Regression5.2 Discriminant Analysis5.3 Further Reading6. Multivariate Analysis of Variance6.1 One-Way Analysis of Variance6.2 Factorial Analysis of Variance6.3 Multivariate Analysis of Variance6.4 Within-Subjects ANOVA and MANOVA6.5 Issues of Trustworthiness in MANOVA6.6 Analysis of Covariance6.7 Further Reading7. Factor Analysis7.1 The Composite Variable in Factor Analysis7.2 Factor Analysis in Action7.3 Issues of Trustworthiness in Factor Analysis7.4 Confirmatory Factor Analysis7.5 Further Reading8. Log-Linear Analysis8.1 Hierarchical Log-Linear Analysis8.2 Trustworthiness in Log-Linear Analysis8.3 Log-Linear Analysis With a Dependent Variable: Logit Analysis8.4 Further ReadingBibliographyIndexAbout the Author

“This book serves as a resource for readers who want to have an overall view of what encompasses multivariate analyses. The author has discussed some important issues rather philosophically (e.g., theory vs. data analysis). These points are valuable even for readers who have extensive training with multivariate analyses.”