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Latent Variable Models: An Introduction to Factor, Path, and Structural Analysis
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.
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.
- GenresResearch
328 pages, Paperback
First published January 1, 1987
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April 19, 2011
This is an accessible survey of structural equation models. This is a technique that, in its fullest version, combines factor analysis with path analysis. It uses maximum likelihood estimation. This is a very potent analytical tool that can provide insights to the dynamics of models. I am a political scientist; I have used SEM to assess what factors affect political phenomena.
This volume? It is readable. Some works feature scores of equations and become difficult for those who are not mathematically well attuned. In the process of reading the book, people will get some sense of different software packages (e.g., LISREL, EQS, or AMOS--the latter of which is the program that I use). There are a small handful of books on SEM that have been particularly useful to me. And this is one of that small number of key works that I depend upon in understanding this tool.
This volume? It is readable. Some works feature scores of equations and become difficult for those who are not mathematically well attuned. In the process of reading the book, people will get some sense of different software packages (e.g., LISREL, EQS, or AMOS--the latter of which is the program that I use). There are a small handful of books on SEM that have been particularly useful to me. And this is one of that small number of key works that I depend upon in understanding this tool.
Displaying 1 of 1 review