ABSTRACT

Focusing on the underlying themes that run through most multivariate methods, in this fully updated 3rd edition of The Essence of Multivariate Thinking Dr. Harlow shares the similarities and differences among multiple multivariate methods to help ease the understanding of the basic concepts.

The book continues to highlight the main themes that run through just about every quantitative method, describing the statistical features in clear language. Analyzed examples are presented in 12 of the 15 chapters, showing when and how to use relevant multivariate methods, and how to interpret the findings both from an overarching macro- and more specific micro-level approach that includes focus on statistical tests, effect sizes and confidence intervals. This revised 3rd edition offers thoroughly revised and updated chapters to bring them in line with current information in the field, the addition of R code for all examples, continued SAS and SPSS code for seven chapters, two new chapters on structural equation modeling (SEM) on multiple sample analysis (MSA) and latent growth modeling (LGM), and applications with a large longitudinal dataset in the examples of all methods chapters.

Of interest to those seeking clarity on multivariate methods often covered in a statistics course for first-year graduate students or advanced undergraduates, this book will be key reading and provide greater conceptual understanding and clear input on how to apply basic and SEM multivariate statistics taught in psychology, education, human development, business, nursing, and other social and life sciences.

part I|38 pages

Overview

chapter 2|23 pages

Background Considerations

part II|49 pages

Intermediate Multivariate Methods with One Continuous Outcome

chapter 3|26 pages

Multiple Regression

chapter 4|21 pages

Analysis of Covariance

part III|62 pages

Multivariate Group Methods with Categorical Variable(s)

chapter 5|24 pages

Multivariate Analysis of Variance

chapter 6|18 pages

Discriminant Function Analysis

chapter 7|18 pages

Logistic Regression

part IV|29 pages

Multivariate Dimensional Methods with Continuous Variables

part V|141 pages

Structural Equation Modeling

chapter 9|19 pages

Structural Equation Modeling

chapter 10|27 pages

Path Analysis

chapter 11|24 pages

Confirmatory Factor Analysis

chapter 12|27 pages

Latent Variable Modeling

part VI|13 pages

Summary