Structural equation modeling : a Bayesian approach / Sik-Yum Lee.
Series: Wiley series in probability and statisticsPublication details: Chichester, England ; Hoboken, NJ : Wiley, ©2007.Description: 1 online resource (xv, 432 pages) : illustrationsContent type:- text
- computer
- online resource
- 9780470024737
- 0470024739
- 9780470024249
- 0470024240
- 519.5/3 22
- QA278.3 .L44 2007
Includes bibliographical references and index.
Structural Equation Modeling; Contents; About the Author; Preface; 1 Introduction; 2 Some Basic Structural Equation Models; 3 Covariance Structure Analysis; 4 Bayesian Estimation of Structural Equation Models; 5 Model Comparison and Model Checking; 6 Structural Equation Models with Continuous and Ordered Categorical Variables; 7 Structural Equation Models with Dichotomous Variables; 8 Nonlinear Structural Equation Models; 9 Two-level Nonlinear Structural Equation Models; 10 Multisample Analysis of Structural Equation Models; 11 Finite Mixtures in Structural Equation Models.
Structural equation modeling (SEM) is a powerful multivariate method allowing the evaluation of a series of simultaneous hypotheses about the impacts of latent and manifest variables on other variables, taking measurement errors into account. As SEMs have grown in popularity in recent years, new models and statistical methods have been developed for more accurate analysis of more complex data.
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