Who would have thought when the first edition of Multivariate Data Analysis was published more than 25 years ago that the use of multivariate statistics would be as pervasive as it is today? During this time we have seen dramatic changes in the research environment faced by both academic and applied researchers.
First, the PC revolution has provided power to the desktop that was unimaginable even just a few years ago. In our time we have gone from punched cards to speech recognition, revolutionizing the way we can interact with and use the personal computer. At the same time we have seen tremendous advances in both the availability of statistical programs and their ease of use, ranging from completely integrated computer packages such as SPSS and SAS to specialized programs for such techniques as neural networks and conjoint analysis. Today researchers can find almost any conceivable technique in a PC format and at a reasonable price.
On the statistical front, we have seen continual development of new techniques, such as conjoint analysis and structural equation modeling. All of these advances, however, have been matched by an ever-increasing need for more analytical capability. The data explosion of recent years has not only taxed our resources to physically handle and analyze all of the available information, but also required a reassessment of our approach to data analysis. Finally, the complexity of the topics being addressed and theory's increased role in research design have combined to require more rigorous and sophisticated techniques to perform the necessary confirmatory analyses.
Chapter 1 Introduction
Chapter 2 Examining Your Data
Chapter 3 Factor Analysis
Chapter 4 Multiple Regression Analysis
Chapter 5 Multiple Discriminant Analysis and Logistic Regression
Chapter 6 Multivariate Analysis of Variance
Chapter 7 Conjoint Analysis
Chapter 8 Cluster Analysis
Chapter 9 Multidimensional Scaling and Correspondence Analysis
Chapter 10 Structural Equation Modeling An Introduction
etc.