<p><p>This new edition surveys the full range of available structural equation modeling (SEM) methodologies. The book has been updated throughout to reflect the arrival of new software packages, which have made analysis much easier than in the past. Applications in a broad range of disciplines are d
Structural equation models: from paths to networks
โ Scribed by Westland, J. Christopher
- Publisher
- Springer International Publishing
- Year
- 2015
- Tongue
- English
- Series
- Studies in systems decision and control
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
An Introduction to Structural Equation Models -- A Brief History of Structural Equation Models -- Partial Least Squares Path Analysis -- LISREL and its Progeny -- Systems of Regression Equations -- Data Collection, Control and Sample Size -- Survey and Questionnaire Data -- Research Structure and Paradigms -- From Paths to Networks: The Evolving Science of Networks.;This compact reference surveys the full range of available structural equation modeling (SEM) methodologies. It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable. This is the first book to present SEM?s development in its proper historical context?essential to understanding the application, strengths and weaknesses of each particular method. This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow in importance in the near future. SEM?s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists. Latent variable theory and application are comprehensively explained, and methods are presented for extending their power, including guidelines for data preparation, sample size calculation, and the special treatment of Likert scale data. Tables of software, methodologies and fit statistics provide a concise reference for any research program, helping assure that its conclusions are defensible and publishable.
โฆ Table of Contents
An Introduction to Structural Equation Models --
A Brief History of Structural Equation Models --
Partial Least Squares Path Analysis --
LISREL and its Progeny --
Systems of Regression Equations --
Data Collection, Control and Sample Size --
Survey and Questionnaire Data --
Research Structure and Paradigms --
From Paths to Networks: The Evolving Science of Networks.
โฆ Subjects
Artificial intelligence;Mathematical physics;MATHEMATICS--Applied;MATHEMATICS--Probability & Statistics--General;Meteorology & climatology;Psychological testing & measurement;Research & development management;Social research & statistics;Structural equation modeling;Electronic books;MATHEMATICS -- Applied;MATHEMATICS -- Probability & Statistics -- General
๐ SIMILAR VOLUMES
An Introduction to Structural Equation Models -- A Brief History of Structural Equation Models -- Partial Least Squares Path Analysis -- LISREL and its Progeny -- Systems of Regression Equations -- Data Collection, Control and Sample Size -- Survey and Questionnaire Data -- Research Structure and Pa
<p><p>This compact reference surveys the full range of available structural equation modeling (SEM) methodologies. It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable. This is the first book to present SEMโs
Latent Variable Models is a simply tremendous statistics book. It is masterfully, and authoritatively written, with a touch of humor here and there. It is -- by far -- the best book on structural equations and related models.
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
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