This book presents the theory and application of Partial Least Squares (PLS) path modeling, a statistical method for analyzing complex relationships between latent variables. The author, Jan-Bernd Lohmöller, provides a comprehensive overview of PLS, its mathematical foundations, and its use in various research contexts. The book is structured into several chapters, starting with an introduction to model building and the distinction between data structure and covariance modeling. It then describes the basic and extended PLS methods, including the algorithmic steps and properties of the PLS approach. The core of the book is devoted to the statistical foundation of PLS, covering topics such as predictor specification, factor score estimation, and the reconstruction of psychometric factor score problems from PLS theory. The author also discusses the relationship between PLS and other methods, such as maximum likelihood (ML) estimation, and the differences between applied and abstract models. The book includes detailed examples and applications, such as the analysis of home environment and intelligence, and the use of PLS in longitudinal data analysis. The author also addresses the extension of PLS to contingency tables and three-mode data cubes, and discusses the implications of these extensions for model interpretation. The book concludes with a discussion of PLS programs and applications, as well as a list of references and indices. The book is written for researchers and students in psychology, education, and related fields who are interested in the application of PLS path modeling.This book presents the theory and application of Partial Least Squares (PLS) path modeling, a statistical method for analyzing complex relationships between latent variables. The author, Jan-Bernd Lohmöller, provides a comprehensive overview of PLS, its mathematical foundations, and its use in various research contexts. The book is structured into several chapters, starting with an introduction to model building and the distinction between data structure and covariance modeling. It then describes the basic and extended PLS methods, including the algorithmic steps and properties of the PLS approach. The core of the book is devoted to the statistical foundation of PLS, covering topics such as predictor specification, factor score estimation, and the reconstruction of psychometric factor score problems from PLS theory. The author also discusses the relationship between PLS and other methods, such as maximum likelihood (ML) estimation, and the differences between applied and abstract models. The book includes detailed examples and applications, such as the analysis of home environment and intelligence, and the use of PLS in longitudinal data analysis. The author also addresses the extension of PLS to contingency tables and three-mode data cubes, and discusses the implications of these extensions for model interpretation. The book concludes with a discussion of PLS programs and applications, as well as a list of references and indices. The book is written for researchers and students in psychology, education, and related fields who are interested in the application of PLS path modeling.