Bookbot

John C. Loehlin

    Latent Variable Models
    Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis
    • This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling more easily. A few sections of the book make use of elementary matrix algebra. An appendix on the topic is provided for those who need a review. The author maintains an informal style so as to increase the book's accessibility. Notes at the end of each chapter provide some of the more technical details. The book is not tied to a particular computer program, but special attention is paid to LISREL, EQS, AMOS, and Mx.New in the fourth edition of Latent Variable * a data CD that features the correlation and covariance matrices used in the exercises;* new sections on missing data, non-normality, mediation, factorial invariance, and automating the construction of path diagrams; and* reorganization of chapters 3-7 to enhance the flow of the book and its flexibility for teaching.Intended for advanced students and researchers in the areas of social, educational, clinical, industrial, consumer, personality, and developmental psychology, sociology, political science, and marketing, some prior familiarity with correlation and regression is helpful.

      Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis2004
      4,4
    • Latent Variable Models

      An Introduction to Factor, Path, and Structural Analysis

      • 328 Seiten
      • 12 Lesestunden

      This book is intended as an introduction to multiple-latent-variable models. Confirmatory factor analysis, path analysis, and structural equation modeling have come out of specialized niches of exploratory factor analysis and are making their bid to become basic research tools for social scientists, including sociologists; political scientists; social, educational, clinical, industrial, personality, and developmental psychologists; and marketing researchers. The author utilizes path diagrams to explain the underlying relationships in multiple-latent-variable models. He also provides an appendix on elementary matrix algebra. The book is not closely tied to a particular computer program or package; however, special attention is paid to two leaders in the field (LISREL and EQS). Users should have access to a latent-variable model-fitting program on the order of LISREL, EQS, CALIS, AMOS, Mx, RAMONA, or SEPATH, and an exploratory factor analysis package such as those in SPSS or SAS. In some places, a matrix manipulation facility such as that found in MINITAB, SAS, or SPSS would be useful.

      Latent Variable Models1998