Description
Book SynopsisFocusing 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 chapte
Trade Review
"Harlow breaks down concepts in simple terms and draws insightful comparisons across different statistical techniques. The text is an excellent resource for all who conduct statistical analyses, from undergraduates to professionals, and everywhere in between."
A. Nayena Blankson, Full Professor of Psychology, Spelman College, USA
"Once again, Harlow writes with authority and great clarity. There’s discussion of estimation, replication, and reproducibility, and all through there’s R code and guidance. This shrewdly revised new edition is a wonderfully future-oriented guide to the multivariate world."
Geoff Cumming, Professor Emeritus, La Trobe University, Melbourne, Australia
"The Essence of Multivariate Thinking provides a gentle introduction to an expansive toolkit of methods with a through line focused on aptly applying them to research questions. Dr. Harlow seamlessly ties together several modeling frameworks (e.g., multiple regression, MANOVA, discriminant function analysis, logistic regression, SEM, and latent growth modeling) by emphasizing commonalities in their underlying assumptions, statistical tests, and effect size interpretations. All this was done with a clear and accessible writing style accompanied by a unifying data example using R, SAS, and SPSS."
Jolynn Pek, Associate Professor of Quantitative Psychology, Ohio State University, USA
"In this third edition of her landmark text on multivariate methods, readers are furnished with ways to think about a variety of multivariate techniques from start to finish: preliminary considerations, testing assumptions, conducting analyses, and writing up and interpreting the results. They will learn how the various multivariate methods are related, and when each should be used. Readers can pattern their own analyses after those used as examples in the book. Her example analyses are easy to follow and emulate.
Every chapter ends by summarizing a topic around a set of core themes to help researchers understand and select appropriate multivariate methods. Professor Harlow is known for her didactic style and ability to communicate complex topics in clear, approachable language. In this third edition she adds new material on multi-sample SEM and latent growth curve models. The provision of R code for all analyses is a welcome addition. Readers will emerge knowing about a variety of multivariate methods—how they are related and distinct, when to use them, how to conduct them, and how to communicate the results to readers. Harlow has a knack for explaining complicated methods in clear, approachable language. In this revised third edition of her landmark text, she provides readers with all the tools they need to become expert users and consumers of multivariate techniques."
Kristopher J. Preacher, Lois Autrey Betts Chair in Education & Human Development, Vanderbilt University, USA
"Lisa Harlow's third edition of The Essence of Multivariate Thinking is the perfect textbook for introductory graduate statistics or a multivariate statistics course. Each chapter provides readers with the foundational knowledge and relevant software code to start implementing the analyses in their own work right away. Harlow's accessible chapters strike the right balance of unique information and related themes."
Alyssa Counsell, Assistant Professor in Quantitative Psychology, Toronto Metropolitan University, Ontario, Canada
Table of ContentsI. OVERVIEW
Chapter 1: Introduction and Multivariate Themes
Chapter 2: Background Themes
II. INTERMEDIATE MULTIVARIATE METHODS WITH ONE CONTINUOUS OUTCOME
Chapter 3: Multiple Regression
Chapter 4: Analysis of Covariance
III. MULTIVARIATE GROUP METHODS WITH CATEGORICAL VARIABLE(S)
Chapter 5. Multivariate Analysis of Variance
Chapter 6: Discriminant Function Analysis
Chapter 7: Logistic Regression
IV. MULTIVARIATE DIMENSIONAL METHODS WITH CONTINUOUS VARIABLES
Chapter 8: Principal Components and Factor Analysis
V: STRUCTURAL EQUATION MODELING
Chapter 9: Structural Equation Modeling
Chapter 10: Path Analysis
Chapter 11: Confirmatory Factor Analysis
Chapter 12: Latent Variable Modeling
Chapter 13: Multiple Sample Analysis
Chapter 14: Latent Growth Modeling
VI: SUMMARY
Chapter 15: Integration of Multivariate Methods
