The Essence of Multivariate Thinking: Basic Themes and Methods

The third edition of The Essence of Multivariate Thinking is a fully updated book that discusses the similarities and differences among multiple multivariate methods to help ease the understanding of the basic concepts. It highlights 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 from an overarching macro- and more specific micro-level approach. The book also includes R code for all examples, 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. It is of interest to those seeking clarity on multivariate methods often covered in a statistics course for first-year graduate students or advanced undergraduates.

Format: Paperback / softback
Length: 344 pages
Publication date: 04 July 2023
Publisher: Taylor & Francis Ltd

Focusing on the fundamental themes that permeate most multivariate methods, this thoroughly revised and updated third edition of The Essence of Multivariate Thinking by Dr. Harlow aims to enhance understanding of the core concepts. The book delves into the similarities and differences among various multivariate techniques, facilitating a clearer grasp of the fundamental principles. It emphasizes the overarching themes that underpin nearly every quantitative approach, presenting statistical concepts in straightforward language. Analyzed examples are showcased throughout 12 of the 15 chapters, illustrating the appropriate application of multivariate methods, as well as how to interpret the findings from both a macro- and micro-level perspective. This revised edition incorporates extensively revised and updated chapters to align with the latest advancements in the field. It includes 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 substantial longitudinal dataset in the examples of all methods chapters.

This book holds particular appeal to individuals seeking clarity on multivariate methods commonly covered in statistics courses for first-year graduate students or advanced undergraduates. It serves as a valuable resource, providing deeper conceptual understanding and offering clear guidance on applying basic and SEM multivariate statistics taught in psychology, education, human development, business, nursing, and other social and life sciences.

Dimension: 254 x 178 (mm)
ISBN-13: 9780367219727
Edition number: 3 ed